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From: kube@cs.ualberta.ca (Ron Kube)
Subject: (Long) August 95 Grad Student's Who's Who in Robotics
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Summary: Monthly posting of Grad Student research in robotics
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Sender: news@ireq.hydro.qc.ca (Netnews Admin)
Organization: Computing Science, U of Alberta, Edmonton, Canada
Date: Tue, 8 Aug 1995 01:38:10 GMT
Approved: mboyer@ireq-robot.hydro.qc.ca, crr@ireq-robot.hydro.qc.ca

[ Is a complete posting necessary, or would a pointer to the ftp and
  WWW sites be enough?  Please send your opinion to
  crr-request@ireq-robot.hydro.qc.ca.  Thanks.  -MB]


August 1995
    >>>>>>>>>>>>>> GRAD STUDENTS WHO'S WHO IN ROBOTICS <<<<<<<<<<<<<<
    =================================================================
Have you ever wondered what grad students are doing in robotics?
A trip to your local research library allows you to see Who's Who
in robotics at the post-doc level, i.e. Professor SoNso, and SuchNsuch,
but what about the graduate students working on their MSc. or PhD?
Here is a summary of the received entries to date.  If you would like to
appear in the Grad Students Who's Who in Robotics send a note to 
kube@cs.ualberta.ca using the 5 point format.  If you have WWW home-page
then include its URL after your name.  This file is available via anonymous
ftp from ftp.cs.ualberta.ca in directory pub/kube as file whosWho, and as a
WWW web page courtesy of Johan Forsberg (jf@sm.luth.se).
http://www.sm.luth.se/csee/ra/sm-roa/Robotics/WhoSWho.html

===============================================================================

1. Name:           Arvin Agah       email: arvin@robotics.usc.edu
2. Supervisor:     George A. Bekey  email: bekey@robotics.usc.edu
3. Institution:    University of Southern California
                   Institute for Robotics & Intelligent Systems
4. Research Area:  Multi-Robot Systems &
                   Biologically-Inspired Robotics
5. Summary:        
                   Investigating the issues of group behavior in 
                   robot colonies, both in simulation and hardware

1. Name:	Peter O Aberg	email: tm90pa@hh.se
		Anders Borghed	email: tm90ab@hh.se
2. Supervisor:	Per-Arne Wiberg	email: pelle@hh.se
3. Institution:	Centre for Computer Architecture, Halmstad University, Sweden
4. Research Area:Future Robotic Control
5. Summary: 
The direct and inverse kinematic problems are fundamental issues in robot 
modelling and control. The direct kinematics is a mapping which allows 
the position of the robot in the cartesian space to be related
with the position in the joint space, i.e. given the position in the joint
coordinates, we can univocally derive, by means of the direct kinematics, the
corresponding position in the cartesian coordinates. 
The kinematic problem is different depending on the structure of the robot. 
For open-chain robotic structures the inverse kinematic poses the most
difficulties and for closed-chain robotic structures it's the opposite.
There are many different techniques for solving the kinematic problems.
Most methods used today are based upon traditional mathematics, such as
Newton-Raphsons method. None of these methods are in any way perfect for the
problem. We have analyzed several different mechanical structures and control 
strategies that are in use today. In our work we also present methods to 
improve robotic motion performance by using new control 
methods and new mechanical structures.

1. Name:	Karl R Altenburg	email: altenbur@plains.nodak.edu
2. Supervisor:	Mark Pavicic		email: pavicic@plains.nodak.edu
3. Institution: North Dakota State University, Fargo, ND, USA
4. Research Area:	Multiple Mobile Robots
5. Summary:

	Investigating the efficiency gains provided by communication and
	memory during multirobot search and retrieval type tasks.  Currently
	tests are being conducted on a set of six small mobile robots, and
	in simulation.  The work also investigates reactive control 
	for individual robots and emergent control for the system.

1. Name : Venkateswara Rao Ayyadevara 	(email : avrao@vax2.concordia.ca)
2. Supervisors : Dr.R.M.H. Cheng	(email : richard@vax2.concordia.ca)
	      Dr.Ramesh Rajagopalan	(email : ramesh@vax2.concordia.ca)
3. Institution : 	Centre for Industrial Control,
		Dept. of Mechanical Engineering
		Concordia University
		Montreal, Canada
4. Research Topic : Development of an Automated Robotic Deburring Workcell for
		 Impeller Blades
5. Summary :
Impeller is a component used in aircraft engines.  Owing to their geometrical
complexity and the rigorous standards specified by air safety regulations, 
impellers are extremely expensive to produce.  After several thousand hours in
use, the blades of an  impeller are warped and the edges are corroded.  If 
some of these impeller blades can be refurbished after being used for several 
thousand hours, considerable amount of money could be saved.  I am working as 
part of a team which is developing an automated workcell using Yamaha Zeta 
Deburring robot to probe the surface of the impeller blade, reconstruct the 
surface, determine the desired edge profile and then use the robot to machine 
the workpiece to obtain that edge profile.  My task is to develop set up for 
probing the surface of the impeller blades and to interface the controller of 
the robot with a PC-transputer network which is responsible for directing the 
probe, surface reconstruction and control of the robot.

1. Name:          Tucker Balch  email: tucker@cc.gatech.edu 
2. Supervisor     Ronald Arkin  email: arkin@cc.gatech.edu 
3. Institution    Georgia Tech
4. Research Area: Communication in Autonomous Robot Societies
5. Summary:

   Multiple cooperating robots are able to complete many tasks more 
   quickly and reliably than one robot alone.  Communication between 
   the robots can multiply their capabilities and effectiveness, but
   to what extent?  In our research, the importance of communication 
   in reactive robotic societies is investigated through experiments 
   on both simulated and real robots.  So far, our research has shown 
   that for some tasks communication can significantly improve 
   performance, but for others inter-agent communication is apparently 
   unnecessary. In  cases where communication helps, the lowest level 
   of communication is almost as effective as the more complex type.  
   Research is being extended to more complex scouting tasks for the 
   Army.

1. Name:  Christian Balkenius email: christian.balkenius@fil.lu.se
          url: http://lucs.fil.lu.se/Staff/christian.balkenius.html
2. Supervisor:  Peter Gardenfors email: peter.gardenfors@fil.lu.se
          url: http://lucs.fil.lu.se/Staff/peter.gardenfors.html
3. Institution:  Lund University Cognitive Science 
	  url: http://lucs.fil.lu.se/
4. Research Area:  Autonomous Robots
5. Summary:
His primary interest is neural network modelling of various forms of
cognitive processes, including sequential processing, induction,
categorisation, motivation and action selection in autonomous agents,
as well as learning of action based spatial representation. Another of
his research areas is how representations can be described from
different perspectives at both the conceptual and the neural level and
the emergent properties in networks of interacting systems for
motivation, perception, action. He is currently working with computer
simulations of neural network controlled artificial creatures and
autonomous mobile robots.

1. Name:            Johan G Benade email: jgb@ing1.rau.ac.za
2. Supervisor:      Andre L Nel    email: aln@ing1.rau.ac.za
3. Institution:     Rand Afrikaans University, Johannesburg, RSA.
4. Research Area:   Autonomous Robotics
5. Summary:
Research is aimed at producing an improved biologically based 
controller for use in hexapod locomotion.  The leg controller must be 
able to cope with uneven terrain - gaps in surfaces - inclines and 
surface tension variability.  At the end of the project a functioning 
hardware realisation must be produced.

1. Name:  Todd M. Bezenek  email: bezenek@plains.nodak.edu
2. Super: Mark Pavicic     email: pavicic@plains.nodak.edu
3. Istit: North Dakota State University, Fargo, ND
4. Area:  Communications for multiple, autonomous robots.
5. Summary:
Several groups are working with multiple robots to collectively
solve a single problem.  Those addressing the problem of communication
between robots are assuming that there exists an unbreakable data path
between each pair of robots, or between each robot and a central
station.  In many real applications where multiple robots may be used,
communication between each pair of robots may not be continuous.  As
the robots move, the network representing pairs of robots that are able
to successfully communicate changes.  My goal is to develop a protocol
which will allow robots on this network to communicate effectively.
I have built two robots which communicate at 1200 baud over a simplex
49Mhz data channel.  A third, which will act as a slave attached to a
PC, is currently being constructed.

1. Name:           Barry L. Brumitt	email:  brumitt+@cmu.edu
			http://www.frc.ri.cmu.edu/~belboz/
2. Supervisor:     Dr. Tony Stentz	email: axs@frc2.frc.ri.cmu.edu
3. Institution:    Carnegie Mellon University
			Robotics Institute, Field Robotics Center
4. Research Area:  Multi-Robot Systems in Unstructured Environments
5. Summary:	   Working on efficient methodologies for optimizing the 
			the motion of multiple agents with respect to 
			the cost of mission completion in situations in which
			the systems knowledge of the world is changing or
			increasing. Both simulation and hardware work on 
			autonomous HMMWV's is underway,

1. Name: William Chesters
         (http://www.dai.ed.ac.uk/students/williamc/williamc.html)
2. Supervisors: Gillian Hayes, John Hallam
3. Institution: Department of AI, University of Edinburgh
4. Research Area: Robot learning with neural networks
5. Summary:

Neural nets look like an interesting approach to `bottom-up' AI, but
if you try to apply them to non-trivial robot tasks, you come up
against some serious problems:

  - a net tends to forget old knowledge as new experiences come in
  - it tends to get stuck in `local minima'
  - it can only work at one timescale: it can't support hierarchies of
    behaviours

I'm interested in getting round these problems by using a community of
competing nets.

1. Name:		Howie Choset		email: choset@robby.caltech.edu
2. Supervisor:		Joel W. Burdick		email: jwb@robby.caltech.edu
3. Institution:		California Institute of Technology
4. Research Area:	Sensor Based Planning for Mobile and Hyper-redundant
			Robots.
5. Summary:
``Sensor Based Planning'' incorporates sensor information, reflecting the
current state of the environment, into a robot's planning process, as opposed
to classical planning, which assumes full knowledge of the world's geometry
prior to planning.  Sensor based planning is important because: (1) the robot
often has no a priori knowledge of the world;  (2) the robot may have only a
coarse knowledge of the world because of limited memory; (3) the world
model is bound to contain inaccuracies which can be overcome with sensor based
planning strategies; and (4) the world is subject to unexpected occurrences or
rapidly changing situations.

Currently, we are working on some initial steps towards path planning 
in a static environment where there is no a priori knowledge.  We are develop-
ing an incremental method to construct a Generalized Voronoi Graph (GVG), which
is a 1-dimensional retract of a bounded space. The GVG is the same thing as
a Generalized Voronoi Diagram in two dimensions. 

Like many other path planning schemes, the distance function is an
integral part of the GVG.  This function is nonsmooth; it is shown
that the non-smoothness occurs at points which are ``critical'' to
many path planning schemes. We have done some nonsmooth analysis on
the distance function which has lead to the incorporation of simple and
realistic sensor models.

1. Name:		Chris Connolly	email: connolly@cs.umass.edu
2. Supervisor:		Rod Grupen
3. Institution: 	Laboratory for Perceptual Robotics,
			University of Massachusetts, Amherst, MA (USA)
4. Research Area:	Motor and task planning using harmonic functions
5. Summary:
    Harmonic functions are solutions to Laplace's equation, and can be
    rapidly computed using resistive networks.  They exhibit no local minima,
    and can be used to generate smooth goal-reaching trajectories [1].
    We're using them for coarse reaching (on P-50 hand/arm systems) and
    mobile robot trajectory planning (on an unmanned ground vehicle).
    The resistive network formulation also turns out to be useful for modeling
    certain nuclei of the basal ganglia [2,3], and provide a theory for
    aspects of motor and cognitive planning in the mammalian central
    nervous system.

    [1] Connolly CI, Grupen RA, (1993) "The Applications of Harmonic Functions 
	to Robotics", Journal of Robotic Systems, 10(7):931-946.
    [2] Connolly CI, Burns JB, (1993) "A Model for the Functioning of 
        the Striatum", Biological Cybernetics, 68(6):535-544.
    [3] Connolly CI, Burns JB, (1993) "A New Striatal Model and 
        its Relationship to
	Basal Ganglia Diseases", Neuroscience Research, 16:271-274.

1.	Name:		Joe Cronin	J.Cronin@UNSW.edu.au
2.	Supervisor:	Richard Frost
			Richard Wilgoss
3.	Institution:	University of New South Wales, Sydney, Australia.
4.	Research Area:	Biped Robot.
5.	Summary.	
I'll make it brief. It will have two legs. It will be anthropomorphic.
It will walk.

The ultimate goal of this project is to design, model and build a biped
robot platform, capable of dynamic motion. It will be hydraulically 
driven, use an HC11 on every joint and stand about four feet high. There
are two main areas of research; the first is to develop and control an
ankle and foot with all degrees of freedom of the human ankle and foot, 
the second is to use distributed HC11's to solve the inverse kinematics
at the joint.

The project is at the stage where construction will begin before the end
of 1993. As the school is in some financial difficulty, I have had to raise
all funds for this project privately. The school does not have an active
mobile robot group, I would be interested in anyone who would be interested
in me.

1. Name:        Sabine Demey       email: demey@mech.kuleuven.ac.be
2. Supervisor: 	Joris De Schutter  email: deschutter@mech.kuleuven.ac.be
3. Institution:	Katholieke Universiteit Leuven, Belgium
4. Research Area: Model-based compliant motion (surface following)
5. Summary:			
A robot equipped with a force sensor (or a camera) has to follow the
surface of a workpiece while maintaining a desired contact force (or
distance) to the surface.
Differential and Euclidean invariant workpiece models, in combination
with on-line matching strategies allow a robust and high quality
(i.e. fast and accurate) task execution in the presence of positioning 
and modelling inaccuracies of the workpiece. 
The matching strategies try to estimate the correspondence between the 
real contact point on the physical workpiece and its counterpart in the model.
Experiments have shown the usefulness of this approach in the case of
following a planar curve. 
Future work includes the development of more efficient matching
strategies and the extension to surfaces.

 1. Name:           John Demiris
                         email: johnde@aifh.ed.ac.uk
 2. Supervisor:     Dr. Gillian Hayes
                         email: gmh@aifh.ed.ac.uk
 3. Institution:    Department of Artificial Intelligence,
                         University of Edinburgh, Scotland
 4. Research Area: Robot Learning by Imitation 
 5. Summary: Humans and certain other types of organisms are capable of 
    learning from others. This type of learning, where agents learn through
    interaction with other members of the group is called social learning.
    My work deals with one particular type of social learning : learning by
    imitation. Imitative learning is difficult to define precisely but it is
    generally interpreted to be learning through observing the behaviour of
    another agent and repeating its actions. In my work I am trying to device
    an architecture that will help us analyze these phenomena, and will 
    allow us to concentrate on the important issue ie. the underlying 
    mechanisms. This will hopefully cut through the chaos in the
    terminology in the relevant ethological literature.  Learning by
    imitation also  allows a robot to learn in terms of its own perceptions and
    capabilities by associating what it is perceiving (in terms of the 
    environment) with what is doing due to its imitation of the
    behaviour of a teacher robot. This promises to ease the process of
    programming many nominally identical robots to perform the same task.

1. Name:		    Bruce Digney		digney@dvinci.usask.ca
2. Supervisor:		M. M. Gupta 
3. Institution: 	Dept. of Mech. Eng., University of Saskatchewan (Canada)
4. Research Area:   Distributed Adaptive Control Systems	
5. Summary:
	In my research I propose that by incorporated learning
	and adaption into a behavior based control system, the skills and
	behaviors which are impossible or impractical to be predetermined
	and embedded can be learned by  the robot during operation.
	The result is a distributed adaptive control system (DACS), which
	can be thought of as the robot's artificial adaptive nervous
	system. This DACS autonomously learns the sensory-response couplings
	between the highest behavioral level, where the desired tasks
	are specified, and the lowest level actuators, which ultimately
	perform those tasks. A DACS has been developed for a simulated
	quadruped mobile robot and extensions to a physical robot
	are planned.

1. Name: Hans Dulimarta		email: dulimart@cps.msu.edu
2. Supervisor:  Anil K. Jain	email: jain@cps.msu.edu
3. Institution: PRIP Laboratory
		Department of Computer Science
		Michigan State University
		East Lansing, Michigan 48824
4. Research Area: Distributed Robotics
5. Summary:

  I address the problem of task decomposition in a mobile robot
  navigation system.  The underlying supposition of my approach is that
  in a typical robot navigation system, there are a number of modules
  running concurrently and each module is assigned a specific subtask.
  In order to accomplish the common goal of the navigation task, these
  modules share the resources and common data in the system.  In such a
  system, resource access control and information sharing among the
  modules must be properly managed.

  In this work, I propose a decomposition of a robot navigation system
  into a number of {\it client} and {\it server} modules.  Resource
  access control, resource sharing, information sharing, and process
  synchronization in the entire robot navigation system are delegated to
  the server modules.  The clients send appropriate requests in order to
  avail of these facilities.  There are two types of server modules
  defined in the system: {\it data server} and {\it hardware server}.
  The core of the system consists of one data server and several
  hardware servers.  The data server acts as a common information
  exchange medium for all the clients, while the hardware servers
  provide access interface to the hardware or peripherals on the robot.
  By decoupling the hardware access routines from the hardware servers,
  the modules in the navigation system can be made independent of
  hardware platform being used.

1. Name:	Sean P. Engelson	email: engelson@cs.uchicago.edu
2. Supervisor:	Drew V. McDermott	email: mcdermott@cs.yale.edu
3. Institution: Yale University
4. Research Area: Map Learning
5. Summary:
   My work explores a `passive' mapping paradigm, in which the
   map-learning system has no direct control over the agent's actions.
   The main problem in map-learning is the fact that the agent's location
   is never perfectly known.  Errors in localization lead inevitably to
   mapping errors.  Passive mapping exacerbates this problem, since the
   mapper cannot perform experiments to verify the robot's location.  My
   approach allows mapping errors to occur, and deals with them in two
   ways.  First, is the use of a graph-based representation scheme which
   incorporates both connectivity and positional information to locally
   bound mapping error.  Second, errors are diagnosed and repaired as
   information becomes available.  The diagnosis and repair strategies
   are based on a taxonomy of possible mapping errors.

1. Name:  Chad English   email: cenglish@mae.carleton.ca
                      URL:  http://cfn.cs.dal.ca/~aa304/Profile.html
2. Supervisor:  Dr. Donald L. Russell
3. Institution:  Carleton University, Ottawa, Canada
4. Research Area:  Impedance control using dual motors
5. Summary:
Current impedance control uses electronic means for controlling 
impedance.  Recent research suggests that a significant increase in 
efficiency could be realized by using physical means to control the 
stiffness and damping of the joints.  The research involves emulating the 
human arm for joint impedance.  Instead of one motor controlling the 
joint there are two, one for pulling in each directions like the bicep 
and tricep of the arm.  The stiffness of the joint is increased by 
turning the two motors in opposite directions to stretch a non-linear 
spring system.

The research and design is focused on use for prosthetics but has 
applications in space robotics, tele-robotics, and any other application 
involving contact tasks.  My thesis proposal is give on my WWW pages.

1.  Name:		Ted C. Feltmeyer  email-tedhead@csd4.csd.uwm.edu
					  email-felt1512@watt.cae.uwm.edu
2.  Supervisor:		Robert Borchelt	  email-borchelt@convex.csd.uwm.edu
			(Dr. Bob)
3.  Institution:	University of Wisconsin Milwaukee, Milwaukee, WI
4.  Research Area:	Automated diagnosis and error recovery in
			robotic workcells using artificial intelligence 
			methods
5.  Summary:		I have worked since August 93 setting up a functional
	robotic workcell with one robot acting as a slave to the other.  At this
	stage, the cell will perhaps perform some sort of electronic assembly
	operations.  This physical system will become a testbed for different
	AI control techniques.  My thesis will come out of the physical system
	setup and initial control using a hybrid expert system.  My dissertation
	will expand further the different control techniques, plus integrate
	vision technology.  The physical system is based on two Adeptone robots,
	AB PLC2/30, and (with luck) a new Pentium based PC.

1. Name: Alex Ferworn                      email: aferworn@watnow.waterloo.ca
2. Supervisor: Deborah Stacey, Andrew Wong email: 
					    dastacey@snowhite.cis.uoguelph.ca
3. Institution: The University of Waterloo Department of Systems Design
                     Engineering
4. Research Area: Learning Autonomous Vehicles (made mostly from junk)
5. Summary: I am currently working on a reinforcement learning architecture
which interacts with a basically reactive control strategy. The problem, as
I see it, is that you can get a purely reactive (call it subsumption) system
to do some really neat and argueably complex things but there seems to be a
line which is very difficult to cross. On the other hand, you have classical
AI systems which can do some really impressive stuff in a very 
constrained environment. Wouldn't it be neat if you could fuse the two? 
Kind of a train as you go architecture. Let the high-level thing make
lots of decisions (even very slowly) and let the low level system tell it
when its wrong and learn from this signal. Currently I am working on 
reinforcement learning schemes for training a 
neural net to modify its behaviour after repeated beatings. I am starting 
off with a modified ARP network and things seem to be moving along. The 
reinforcement signal comes from a purely reactive system. Don't know how
it will turn out. Call the whole thing Reflexive Instructor/Deliberate 
Apprentice (RI/DA) :-)

1. Name:		Johan Forsberg		email: jf@sm.luth.se
2. Supervisor:		Ake Wernersson
3. Institution:		Robotics & Automation
			Lulea University of Technology
			S-971 87 LULEA, SWEDEN
4. Research Area:	Autonomous Robots
5. Summary:

I'm currently working with statistical map representation where the
robot builds the map autonomously from measurements taken by a
scanning range measuring laser. This statistical map is mainly
intended for localization, while some other approach might be
better for path planning. I think that to create an autonomous robot,
we should not try to mimick the way humans, or animals, work. A better
approach is to look at what computers are good at, and how this can be
used to make a better robot. One example: when entering a room, we can
know which room we are in either by recognizing the way the room
looks, or by knowing exactly what route we took to get there (in
meters and millimeters). The first method is the main method for
humans, but extremely difficult for a computer. The second is difficult
for a human, but easy for a robot.

1. Name:		Milind Ghanekar  email: ghanekar@kingcong.uwaterloo.ca
			http://sunee.uwaterloo.ca/~mghaneka/
2. Supervisor:		D.W.L Wang       email: dwang@kingcong.uwaterloo.ca
			G.R. Heppler     email: heppler@dial.uwaterloo.ca
3. Institution: 	Dept. of Electrical and Computer Engineering,
			University of Waterloo, Waterloo, Ontario, Canada.
4. Research Area:	Scaling Laws for Controllers of Dynamically Equivalent 
			Flexible Robotic Manipulators
5. Summary:
        This research involves determining the conditions which define 
	dynamic equivalence for a general n-link robotic manipulator.
	Given a set of dynamically equivalent manipulators, the idea
	then is to design a single nondimensional controller for the set, 
	and be able to scale this controller appropriately to apply to
	any particular manipulator within the set.  
	This theory has implications in the construction of large-sized
	robots.  Using the dynamic equivalence conditions, a smaller version
	of the actual robot can be constructed.  All the analysis, debugging,
	and controller design can then be done economically on the small 
	prototype robot with the knowledge that the results can be scaled 
	to apply to the actual larger robot.  
        The dynamic equivalence conditions for a single flexible link 
	manipulator have been determined, and a control law for frequency
	domain controllers was developed.  This theory was successfully
	verified experimentally.  Current work involves determining the
	dynamic equivalence conditions for a five-bar linkage robot.

1. Name: 		Fredric M. Gold e-mail fgold@wpi.wpi.edu
2. Supervisor:  	John J. Bausch
3. Institution:		Worcester Polytechnic Institute, Worcester, MA
4. Reasearch Area:	Brush-based Active Robotic Deburring of Large Castings
5. Summary:		Deburring is the removal of unwanted material left
after a machining process.  Manual deburring is the most expensive form of
deburring and the most widely used.  By using a robot as a positioning tool
for the active end-effector the process can be done less expensive, more 
repeatable, faster, and with less rework necessary.  The use of brushes, rather
than rotary files, simplifies the control strategy of the end-effector.  
Discrete control has been found to give repeatable rounded edges with the
burrs removed.  Simulation of the process has also been performed using two
3-D modeling packages, CATIA and I-DEAS.  The simulation can be used for 
effective production planning of the whole process.

1. Name: Bill Gribble email: grib@mamba.asg.arlut.utexas.edu
2. Supervisor: Ben Kuipers email: kuipers@cs.utexas.edu
3. Institution: University of Texas AI Lab
4. Research area: Distributed architectures for visually guided mobile robots
5. Summary: A robotic platform capable of manipulating increasingly
large amounts of sensory data while still meeting real-time
performance constraints must diverge from a monolithic model of
computation.  With a moderate number of compute nodes, each
specialized for a task, the problem of sensor data partitioning can be
more easily attacked.  We are constructing a robot consisting of a
number of nodes, including general-purpose microprocessors, small
microcontrollers, and DSP engines, each with its own purpose, all
linked by a 32Mbps custom local network.  The software architecture is
based on a packet protocol similar to that used in dataflow parallel 
machines. 

1. Name:           Lyle Hall        email: hall@cs.uiuc.edu
2. Supervisor:     Sylvian Ray      email: ray@cs.uiuc.edu
                   Fred Delcomyn           delcomyn@ux1.cso.uiuc.edu
3. Institution:    University of Illinois at Urbana-Champaign
4. Research Area:  Robot Simulation and Control of Insect-like Walking 
5. Summary:        Developing a dynamic simulator and controller to model
		   walking in cockroaches.

 1. Name: Bridget Hallam <bridget@aifh.ed.ac.uk>
 2. Supervisor: Gillian Hayes
 3. Institution: Dept of Artificial Intelligence, Edinburgh University, UK
 4. Research Area: Controlling Robots using Biological Theories
 5. Summary:

   Studying animal behavioural control can give insights into autonomous
   behaviour that may prove useful for those wishing to build autonomous
   robots. Implementing Halperin's neuro-connector model of learning and   
   motivation on a mobile robot has shown that it can be used to control 
   robots, and that it is reasonably complete. Implementation in simulation
   will discover the sensitivity of the various features to variations in 
   parameters and the exact equations used, and so improve the model as a
   robot controller. It may also improve the model for ethologists.

1. Name:	   Roger B. Hertz	(hertz@ecf.toronto.edu)
2. Supervisor:	   Peter C. Hughes	(hughesp@ecf.toronto.edu)
3. Institution:	   University of Toronto Institute for Aerospace Studies
4. Research Area:  Articulated-Truss Manipulators
5. Summary:
	We are investigating the use of articulated truss mechanisms
	for both space and terrestrial robotics applications.  We have
	constructed a prototype manipulator based on this concept that
	is capable of 3-DOF spatial motion.  My research is centered
	on applying the technology to a 6-DOF industrial version of the
	manipulator.  Current work is involved with manipulator design, 
	development of kinematics algorithms, workspace analysis, and 
	customization of an industrial robot contoller.

1. Name:  Frank Hoffmann 	email: hoefi@ang-physik.uni-kiel.de 
          url: http://www.ang-physik.uni-kiel.de
2. Supervisor: Gerd Pfister 	email: gerd@ang-physik.uni-kiel.de            
3. Institution: Institute for Applied Physics, University Kiel
4. Research Area:  Autonomous Agents, Fuzzy Logic, Genetic Algorithms
5. Summary: I have developed a new design method for a fuzzy logic controler
   using genetic algorithms.
   I have applied my method to the design of an autonomous agent
   for a real world vehicle equipped with ultrasonic sensors. 

1. Name:	Tomas Hogstrom  	email: tomas@idefix.ikp.liu.se
2. Supervisor:	Ake Wernersson  	email: -
3. Institution: RAMeS, Linkoping Inst. of Tech, Linkoping, Sweden
4. Research Area: Supervisory controlled (mobile) robots
5. Summary:
	I'm looking at supervisory controlled robots, i.e. an operator sends commands / instructions to the remote robot which is to autonomous execute the given subtask. I have built a robot with a turnable camera and a rate gyro, and have investigated what is possible to do with this (simple) sensor combination. I will probably add a laser range scanner for autonomous wall/corridor following. Our sister group has developped algorithms for that. (Robust navigation using the Hough transform). I'm also interested 
in using virtual reality, but I'm not sure we have enough resources for such a project.
We have my robot, and a Robosoft Robuter, some range measuring lasers, two inertial sensor systems, range cameras.

The other students in my group works with:
Inertial navigation, surface estimation. - Bengt Boberg
Reducing ambiguites from reflective and/or transparent objects when using a laser range camera. - Jonas Nygaards
Dual Control, exploratory moves, dynamic programming. - Bernt Nilsson

1. Name:           Angelos KARAKEREZIS,Dipl-Ing,ME,MSc,DIC,IMEng
		   e-mail:a.karakerezis@bristol.ac.uk
2. Supervisor:     Professor Koorosh KHODABANDEHLOO
		   e-mail:k.khodabandehloo@bristol.ac.uk
                   Director of A.M.A.R.C.
3. Institution:	   Advanced Manufacturing and Automation Research Centre
		   University of BRISTOL, Faculty of Engineering
		   Queen's Building, University Walk, Bristol, BS8 1TR, UK
		   Tel: +44 (272) 288213,257126,257128
		   Fax: +44 (272) 257127		
4. Reseacrh area:  Robotic handling of flexible non rigid materials
5. Summary:	   Examining robotic handling of flexible viscoelastic non 
		   rigid materials using a discrete element method.

1. Name:           Juergen Karner       email: juergen@lpa.uni-sb.de
2. Supervisor:     H. Janocha
3. Institution:    University of Saarland
		   Institute for Process Automation
4. Research Area:  Hybrid Control of Robots with Fuzzy Logic
5. Summary:        Existing robots use PID-controllers.
		   The parameters of the PID-controllers are fixed and
		   do not change depending on the actual pose of the
		   robot. We want to change the parameters of the 
		   PID-controllers using fuzzy-logic.

1. Name:           Zunaid Kazi      email: kazi@asel.udel.edu 
2. Supervisor:     Richard Foulds   email: foulds@asel.udel.edu
                   Daniel Chester   email: chester@cis.udel.edu
3. Institution:    University of Delaware
                   Applied Science and Engineering Laboratories
4. Research Area:  Multimodal User Supervised Interface and
                   Intelligent Control (MUSIIC) of a Telerobot.
5. Summary:        
We describe a method and system which integrates human-computer
interaction with reactive planning to operate a telerobot for use 
as an assistive device. The system is intended to operate in an 
unstructured environment, rather than in a structured workcell, 
allowing the user considerable freedom and flexibility in terms 
of control and operating ease. Our approach is based on the 
assumption that while the user's world is unstructured, objects within
it are reasonably predictable. We reflect this arrangement by providing 
a means of determining the superquadric shape representation of the 
scene, and an object-oriented knowledge base and reactive planner 
which superimposes information about common objects in the world. 
A multimodal user interface interprets deictic gesture and speech 
inputs with the objective of identifying the objects in the work space 
that are of interest to the user. The multimodal interface performs 
a critical disambiguation function by binding the spoken words
to a location in the physical work space. The spoken input is also 
used to supplant the need for general purpose object recognition using a
hierarchical object-oriented representation scheme. The result is an 
instructible telerobot which integrates speech-deictic gesture control 
with a knowledge-driven reactive planner and a stereo-vision system 
to acquire the work space model. 

 1. Name: Taehee Kim <taehee@aifh.ed.ac.uk>
 2. Supervisor: Chris Malcolm
 3. Institution: Dept of Artificial Intelligence, Edinburgh University, UK
 4. Research Area: Sensor Fusion
 5. Summary: Focusing on the benefits of biological sensors and the
sensor utilisation scheme, my research is aiming at implementation of a
flexible control structure co-ordinating multiple sensors for assembly
robots. Skin-like sensors have been developed. Application of the
sensors are being investigated.

1. Name:  C. Ronald Kube    email: kube@cs.ualberta.ca
          url: http://web.cs.ualberta.ca/~kube/
2. Supervisor:	H. Zhang  email: zhang@cs.ualberta.ca
3. Institution: University of Alberta, Alberta, Canada.
4. Research Area:  Collective Robotics
5. Summary:
This research examines the question:  Can autonomous mobile robots achieve
tasks collectively?  We begin with the study of social insects--Nature's
example of a decentralized control system--simulating those mechanisms that 
could prove useful in controlling teams of robots. Proposed theories are 
then tested on situated physical robots.  To date, a system consisting of 5 
mobile micro-robots have been built and used in a box-pushing task [1].  The
reactive architecture is implemented in simple combinational logic, with
behaviour arbitration trained using an Adaptive Logic Network (ALN) [2].
Currently, a new system of 10 micro-robots are being constructed to extend
the box-pushing task to transporting [3].  Recent work has addressed the
problem of stagnation recovery in reactive systems [4].

[1] Kube CR, Zhang H, (1992) "Collective Robotic Intelligence," 
    Second International Conference on Simulation of Adaptive Behavior, 460-468.
[2] Kube CR, Zhang H, Wang X, (1993) "Controlling Collective Tasks With an ALN,"
    International Conference on Intelligent Robots and Systems IROS, 289-293.
[3] Kube CR, Zhang H,(1994) "Collective Robotics: From Social Insects to 
    Robots," Adaptive Behavior, 2(2), MIT Press, 189-219.
[4] Kube CR, Zhang H, (1994) "Stagnation Recovery Behaviours for Collective
    Robotics," International Conference on Intelligent Robots and Systems.

1. Name:	   Gerard Lacey	        email: gerard.lacey@cs.tcd.ie
   url:  http://cvg.cs.tcd.ie/gjlacey/doc/personal/personal.html
2. Supervisor:	   Dr. Ken Dawson-Howe	email: ken.dawson-howe@cs.tcd.ie
3. Institution:    Trinity College Dublin, Dublin 2, Ireland.
4. Research Area:  Autonomus and Semi-autonomus Mobile Robotics
5. Summary:	   Developoment of a low cost multi sensor autonomus 
      robot platfrom, intended to provide a base for further research 
      into autonomus and semi autonomus robotic research.  The future 
      research work is focused on using exploritory moves to help remove 
      uncertianties in the perception of the robots environment.

1. Name:           Dimitrios Lambrinos  email: lambri@ifi.unizh.ch
   URL: http://josef.ifi.unizh.ch/groups/ailab/people/lambri.html
2. Supervisor:     Rolf Pfeifer         email: pfeifer@ifi.unizh.ch
3. Institution:	   Dept. of Computer Science
   		   University of Zurich
         	   Winterthurerstrasse 190
         	   CH - 8057 Zurich, Switzerland
4. Research Area: Developing Biologically inspired Navigation 
		  mechanisms for "Real" Autonomous Mobile Agents
5. Summary:
	Probably the most fundamental requirement of autonomous mobile
	agent is navigation. One of the fundamental problems in robotics
	navigation is that of localisation. The agent must be able to 
	determine its relationship to the environment, and because we
	are talking about "autonomous agents", it has to do this by
	its own means, that is to say, by its sensors. 
	The majority of the literature on map building is devoted to 
	approaches involving a global absolute coordinate frame. We
	believe that since the real world is never static, and once there are
	errors, it is impossible in a complex and dynamic environment for an
	autonomous agent to build and maintain a globally metrically accurate
	map through exploration. Any approach that utilizes
	exclusively quantitative representations is not compatible with our
	approach since we are avoiding Cartesian-like concepts of
	spatial representations which are condemned to suffer from the
	frame of reference problem.
	As a start we propose a scheme that is a combination of
	two mechanisms: A cheap dead-reckoning mechanism for long distances and
	Landmark navigation at a certain point (pin-point navigation) when 
	the agent is close to the "Nest".

1. Name:        David E. Lee		email: dlee@cs.ucla.edu
2. Supervisors: Michel A. Melkanoff	email: mam@cs.ucla.edu
		H. Thomas Hahn		       hahn@seas.ucla.edu
3. Institution: University of California, Los Angeles, CA, USA
4. Research Area:	Force Control & Mating Models for Component-Component
			Interactions During Product Assembly Simulation
5. Summary:

	This research focuses on the development of force control models and
	representations of the dynamics of component-component interactions
	to predict and simulate mating conditions during product assembly.
	These analytic models are sought in order to provide a theoretical
	underpinning to virtual assembly production analysis - assessing
	assembly feasibility and the reliability of mating conditions prior
	to the physical realization of individual components and actual
	assembly of a product.

1. Name:             David Lee         email:D.Lee@cs.ucl.ac.uk
2. Supervisor:       Michael Recce     email: M.Recce@anat.ucl.ac.uk
3. Institution:      Computer Science Department, University College
London, U.K.
4. Research Area:    Exploration Strategies for Mobile Robots
5. Summary:
How should a mobile robot move about its environment in order to
construct a high-quality world model (map) as efficiently as
possible? This research addresses this question through
experimentation with a sonar-equipped mobile robot. An essential
sub-question is how to judge the quality of a map. A novel quality
metric is defined for this purpose, using the robot's map to predict
its success at executing a set of benchmark tasks. This metric is then
used to examine and evaluate a number of exploration strategies
which vary from purely reactive wall-following to more complex
strategies which make full use of the information held in the map at
each stage of the exploration.

1. Name:                Wan-Yik Lee          email: wylee@cs.utexas.edu
                          URL: http://www.cs.utexas.edu/~wylee
2. Supervisor:          Benjamin J. Kuipers  email: kuipers@cs.utexas.edu
                          URL: http://www.cs.utexas.edu/~kuipers
3. Institution:         Artificial Intelligence Lab, 
                          URL: http://www.cs.utexas.edu/~qr/robotics.html
			University of Texas at Austin
                        Department of Computer Sciences
			Austin, TX 78712
4. Research Area:       Autonomous Mobile Robot Exploration, Mapping 
                        and Navigation using the Spatial Semantic Hierarchy 
		        (SSH) approach.
			Intelligent Control.
			
5. Summary:   

The Spatial Semantic Hierarchy approach to robot exploration and
mapping has been developed in the context of a simulated robot, NX,
and tested on simulated environments with very simple models of
sensorimotor errors [Kuipers and Levitt, 1988; Kuipers and Byun, 1988,
1991].  Physical implementations of aspects of the SSH approach have
been built by other researchers but they do not provide adequate
demonstration of its strengths or adequate analysis of its conditions
of applicability. My research will be to extend the SSH Mapping theory
from its original prototypical version to a version adequate for
handling real sensorimotor interaction with a real (office)
environment. The extended theory will be implemented on a physical
robot to explore a previously unknown environment, and to create a SSH
spatial description of the environment. 

More in my proposal 
   URL: http://www.cs.utexas.edu/~wylee/my-phd-proposal-abstract.html

----------------------------------------------------------------------------

1. Name:	Tsai-Yen Li	email: li@flamingo.stanford.edu
		URL: http://robotics.stanford.edu/users/tli/bio.html
2. Supervisor:	Jean-Claude Latombe
		URL: http://robotics.stanford.edu/users/latombe/bio.html
3. Institution:	Computer Science Robotics Laboratory, Stanford University 
		URL: http://www.stanford.edu/stanford.html
4. Research Area:	On-line Robot Motion Planning
5. Summary:

I'm interested in robot motion planning in general. My current
research emphasize on how to bring robot motion planning on-line for
dynamic environments. More specifically, I consider the scenario of a
compact robotic workcell equipped with two SCARA-type manipulator arms
fetching objects from a conveyer belt. The geometry of all the objects
in the workspace is known in advance but everything else can be
changed on-line. The problem is challenging since planning can only
take very small amount of time before objects leave the workspace, and
the planning time needs to be accounted for during the planning
process. We approach this on-line multi-arm manipulation planning
problem by decomposing the problem into four subproblems for which we
developed very fast planning primitives. We have implemented our
algorithm in software that simulates the robot motion and tests the
on-line performance of our planner.

1. Name:           Douglas C. MacKenzie    email: doug@cc.gatech.edu
Mosaic URL "file://ftp.cc.gatech.edu/pub/ai/students/doug/Doug.MacKenzie.html"

2. Supervisor:     Ronald C. Arkin         email: arkin@cc.gatech.edu
3. Institution:    Georgia Institute of Technology, Atlanta, Georgia, USA
4. Research Area:  Behavioral planning, mobile manipulation.
5. Summary:
Behavior-based robot architectures are systems where the overt behavior
of the system emerges from the complex interactions of numerous simple
sensorimotor behaviors.  The distributed nature of the overt behavior
generation enormously complicates the problem of configuring the system
to generate a desired overt behavior.  Instead of modifying a single
object, a set of sensorimotor behaviors must be selected and parameterized
(a configuration) such that an appropriate overt behavior is manifested.  
This research will automate the process of generating a behavior configuration
by creating an interactive, graphically based, configuration designer.  The
designer will function as an assistant, capable of pointing out areas of the
design intentions which are not met by the current configuration, suggesting
additions, deletions, and modifications, as well as insuring syntactic
validity, semantic validity, and sufficiency of the final design.
Configurations will be represented in the Configuration Description
Language (CDL), a context free language which has been developed to allow
compact, exact description of individual robot configurations as well as
the interactions of societies of cooperating mobile robots.  An optimizer
module will verify that each member of the generated configuration is
necessary, and also that the resulting configuration is sufficient with
respect to the designer's intentions.  Architecture specific code generator
modules will allow generating C code using various methodologies 
(i.e. Subsumption, Schemas, etc.).

Name: Amol Dattatraya Mali
Supervisor: Amitabha Mukerjee. ( amit@iitk.ernet.in )
Institute: Centre For Robotics,
	   Indian Institute of Technology, Kanpur,
	   Uttar Pradesh, India, 208016.       
SUMMARY:
We have identified stimulus overgeneralization as the cause of
cyclic behaviour. We have analyzed cyclic conflict in this research.
We have adopted a 3-tuple model of behaviour in which we express
a behaviour module by < s, a, c> where s is stimulus, a denotes
action and c denotes the consequence. We have developed a notation
for power, usefulness, flexibility of behaviours. In practice to do
tasks behaviours need to be triggered in a particular sequence where
stimulus of each behavioural module in the chain is implied by the
consequence of the module immediately preceding it. A cyclic conflict 
occurs when the consequence of a module later in the temporal chain of 
behaviours triggers its stimulus or stimulus of some module before it 
in the chain and the cycle is not terminated by suppression by higher 
level modules or by a termination condition. The cycle detection 
strategy that we have used is of forming a temporal graph of behaviours
based on action sequences and performing graph search. 
The solutions that we have proposed to eliminate the cyclic conflict
are (1) specialize the stimulus of module earlier in the chain 
so that the consequence of module later in the chain does not trigger it.
(stimulus specialization)
(2) Modify the action of module later in the chain so that its consequence
does not trigger the stimulus of module earlier in the chain. (response
generalization).

Name:		 Chris Manson  (cmanson@oboe.calpoly.edu)
Supervisor:	 Jens Pohl
Institution:	 Calif. Polytechnic State Univ. at San Luis Obispo
		 College of Architecture and Environmental Design
Research Area:	 Hostile environment R.O.V.'s

Summary:  This is a solo design/fabrication Master's project implemented 
by myself to produce a low cost (under $12,000) disposable or "suicide" 
radio controlled tracked platform which could be used for hostile 
environment observation and recon. The platform could then be kept for 
further missions, or left in military or other environmental "hot 
zones" where retrieval would cease to be cost effective. Upon completion, 
the 300lb. unit will be able navigate stairs up to 28 degrees, and be 
controlled by a commercial R/C unit aided by wireless video.		

1. Name:           Marinus Maris  email: maris@ifi.unizh.ch
   URL: http://josef.ifi.unizh.ch/groups/ailab/people/maris.html
2. Supervisor:     Rolf Pfeifer         email: pfeifer@ifi.unizh.ch
3. Institution:	   Dept. of Computer Science
   		   University of Zurich
         	   Winterthurerstrasse 190
         	   CH - 8057 Zurich, Switzerland
4. Research Area:  Autonomous Robots, Path Planning
5. Summary:
	To understand and design a real autonomous robot several 
	aspects need to be investigated. The main research strategy
	focusses on adaptive control structures to enable the robot to 
	manipulate its maneuvering around in the environment. As an
	example we have designed a robot that avoids obstacles
	utilizing just one sensor.

1. Name:		Simon P. Monckton   email:monckton@mech.ubc.ca
2. Supervisor:		D. Cherchas	email: cherchas@cs.ualberta.ca
3. Institution: 	University of British Columbia, B.C., Canada.
4. Research Area:	Multiagent Robotics
5. Summary:
     Most industrial manipulators employ a mapping between joint space
     and cartesian space either in the form of an inverse kinematic solution
     or the Jacobian inverse.  This approach has evolved
     out of the understanding of kinematics and dynamics of mechanisms and now
     is the exclusive manipulator control methodology. 
     Unfortunately, these approaches require significant support by world and 
     dynamic models to achieve robust performance under varying environmental 
     conditions. Furthermore, redundant manipulation often makes
     these approaches impractical to the point where few
     manufacturers consider the development of manipulators with greater than 6
     d.o.f.. This research addresses a new possibility, a cooperative 
     architecture of intelligent agents contributing toward the pursuit of a 
     global objective while pursuing local objectives. A literature survey 
     and early  simulations indicate that this approach
     not only viable, but less compute intensive than existing adaptive 
     and redundant control methods. 

1. Name:           Jonathan Monsarrat       email: jgm@cs.brown.edu
2. Supervisor:     Tom Dean                 email: tld@cs.brown.edu
3. Institution:    Brown University
                   Department of Computer Science
4. Research Area:  Robot navigation: planning and learning
5. Summary:        Planning in Markov domains, sensor fusion,
                   networking, simulation, and API software for robotics

1. Name         	Jane Mulligan (mulligan@cs.ubc.ca)
2. Supervisor   	Alan Mackworth (mack@cs.ubc.ca)
3. Institution  	University of British Columbia, B.C., Canada
4. Research Area	Integration of Sensing and Action
5. Summary
	My work looks at the sensory and model information
	required to achieve robotic tasks and proposes a layered structure
	for integrating sensing and action. Layers are organized based
	on the increasing informational/environmental complexity of 5 
	basic classes of tasks.

1. Name: Luis Alberto Munoz Ubando email: munoz@lifia.imag.fr
          url: http://cosmos.imag.fr/SHARP/Munoz/home-fr.html
2. Supervisor:  Christian Laugier email: laugier@lifia.imag.fr
3. Institution: Laboratoire de Informatique Fundamentale et de Intelligence Artificielle
        IMAG - Institut National Polytechnique de Grenoble - FRANCE
4. Research Area:  Dexterous Manipulation, real-time control and planning, robotic hands.
5. Summary: I am working on the planning and control strategies for dexterous manipulation using real robotic hands.

NAME :            Elizabeth Nitz     enitz@mines.colorado.edu
SUPERVISOR :      Dr. Robin Murphy    rmurphy@mines.colorado.edu
INSTITUTION :     Colorado School of Mines, Golden, Colorado
RESEARCH AREA :   Multiple Mobile Robotics & Communication
SUMMARY :         Current work focuses on constructing a new
                  collaborative robot architecture consisting
                  of one computationally-powerful "master" robot,
                  who learns all it needs to know about a particular
                  environment and possibly produces plans, 
                  and multiple less-powerful "apprentice" robots
                  who then use the knowledge gathered by the master 
                  to carry out the plans or tasks within the environment.
                  This type of system should combine the robustness of
                  multiple homogeneous robots via redundancy with the 
                  cost-efficiency (and possibly disposability) of simple    
                  robots, and at the same time use the latest in
                  computationally-intensive perceptual algorithms
                  for learning.  The target application is exploration 
                  and monitoring of hazardous or unfriendly environments.

1.- Name:        Vicente Parra-Vega     email:vega@arimotolab.t.u-tokyo.ac.jp
2.- Supervisor:  Suguro Arimoto         email:
3.- Institution: University of Tokyo, Tokyo, Japan
4.- Research Area:    Control of Robot (adaptive/VSS/discontinuous/robustness)
5.- Summary:
	The research has focused on controlling robot manipulator for
free (position) and constrained motion (force/position) as well by
means of nonlinear techniques. Adaptive control. Discontinuous
adaptive control. Variable structure control. Adaptive VSC. PD. 
Robustness. Stability (asymptotic and exponential). It takes into
account the nonlinear model of the robot manipulator plus friction
forces and the dynamics of the motor at each joint. No experiments,
only theoretical work and computer simulations.

 1. Name:		Miles Pebody.	e-mail: M.Pebody@cs.ucl.ac.uk
 2. Supervisors:	John Campbell.	e-mail: J.Campbell@cs.ucl.ac.uk
			John Gilby.	e-mail: 100115.624@compuserve.com
 3. Institution: 	University College London, UK.
 4. Research Area:	Applied intelligent sensing and control
 5. Summary:
	
     My project deals with aspects of intelligent sensing and control
in a system of functionally and physically distributed control
elements that are embedded and situated in a real-world environment.
The system is an active laser scanning sensor device used in industry
for analysing and detecting defects in products such as glass, plastic
film, metal and painted surfaces which are moved through its laser
beam. Reflected laser light is detected by a number of different
sensors and information interpreted to locate and identify defects.
This in turn can be used to direct the production process to deal with
any critical situation detected. The aims of the project are to
develop and explore the nature and effectiveness of the techniques
used in Behaviour Based Artificial Intelligence when applied to a real
world environment other than that of mobile robotics.  The initial aim
of the work is to develop a Subsumption Architecture based control
mechanism and then to expand on initial results by exploring aspects
of agent cooperation and learning. New control strategies will be
experimented with which aim to increase the reliability and robustness
of the system.

1. Name:	   Simon Perkins
			email: S.Perkins@ed.ac.uk
			WWW: http://www.dai.ed.ac.uk/students/simonpe/
2. Supervisor:	   Gillian Hayes
			email: gmh@aifh.ed.ac.uk
3. Institution:	   Department of Artificial Intelligence,
			University of Edinburgh, Scotland
4. Research Area:  Learning in mobile robots
5. Summary:
		   `Shaping' robots. i.e. How can a human designer
		   with a priori knowledge about how a task should be
		   performed and decomposed, use that knowledge to
		   construct a training program for a robot that
		   allows it to learn that task efficiently and
		   quickly via (probably) reinforcement learning.

 1. Name: Giovanni Cosimo Pettinaro <giovanni@aifh.ed.ac.uk>
 2. Supervisor: Chris Malcolm
 3. Institution: Dept of Artificial Intelligence, Edinburgh University, UK
 4. Research Area: Behaviour Based Approach in Assembly Robots
 5. Summary:
        Investigating the existance of a set of atomic behaviour with which
        describing any kind of more complex behaviour. 

Name : Ranganathan Ramanathan (AKA Rungun) email : ramanath@asel.udel.edu
Supervisor : Dr. Rahmim Seliktar  &        email : seliktr@duvm.ocs.drexel.edu
             Dr. Tariq Rahman              email : rahman@asel.udel.edu
Institution : Drexel University, MEM department, Philadelphia, PA 19014, USA
Research Area :  Rehabilitation Robotics
Summary :
     Design and development of powered orthosis.  Stuck at an interesting but
     tough problem of finding out an GOOD anti-gravity mechanism to use.  Then
     we power this mechanism, and look into various control issues  and human
     machine interface.

1. Name:           P. Douglas Reeder   email: reederp@er4.eng.ohio-state.edu
2. Supervisor:     David Orin          email: orin@er4.eng.ohio-state.edu
3. Institution:    Ohio State University
                   Department of Electrical Engineering
                   http://eewww.eng.ohio-state.edu/
4. Research Area:  Legged Locomotion (Walking Machines) &
                   Navigation in Natural Environments
5. Summary:        Investigation the architectures neccesary for dynamic
                   legged locomotion (balancing) and navigation in 
                   real-world environments

1. Name:	Dan S Reznik		email: reznik@robios.me.wisc.edu
2. Supervisor:	Vladimir Lumelsky	email: lumelsky@robios.me.wisc.edu
3. Institution: University of Wisconsin-Madison, Madison, WI, 53706, USA
4. Research Area:	Sensor-based motion planning for
			highly-redundant kinematic structures
5. Summary:
I am working on the design of sensor-based algorithms for
for highly-redundant robots -- so far I have considered
snake-shaped robots, multi-finger hand with lots of links per
finger, and "multi-branch" snakes, which are tree-shaped robots with
lots of degrees of freedom. We consider both planar and 3D
structures.

1. Name:   Paulo F. F. Rosa  email: paulo@i2es1.info.eng.niigata-u.ac.jp
2. Supervisor: Tokuji Okada  email: okada@i2es1.info.eng.niigata-u.ac.jp
3. Institution:    Niigata University
                   Information Engineering Department
4. Research Area:  Dexterous Manipulation &
                   Intelligent Sensors for Robotics
5. Summary:        
Currently I am developing the background theory and initial hardware and 
control of a new family of two-finger non-articulated hands named 
SCROLLIC gripper (acro nym for synchronously closing with rolling constraints). 
These grippers exploit  rolling at the multiple point-contacts available,
aimed at firm grasps, through the control of the rotation and translation of the
fingertips within a grip.  The  ultimate goal is to provide the parallel-jaw 
with dexterity skills similar to those of an articulated multi-fingered hand.

1. Name:		Julio Kenneth Rosenblatt	email: jkr@ri.cmu.edu
2. Supervisor:		Chuck Thorpe			email: cet@ri.cmu.edu
3. Institution: 	Robotics Institute, Carnegie Mellon University
			Pittsburgh, PA, USA
4. Research Area:	Mobile Robot Architectures
5. Summary:
The Distributed Architecture for Mobile Navigation (DAMN) provides a
framework for independent, distributed, task-achieving behaviors,
similar in spirit to the Subsumption Architecture. One important
difference between DAMN and the Subsumption Architecture is that
rather than one behavior overriding another, DAMN behaviors send
weighted votes to an arbiter wheich then selects the action that best
satisfies several objectives concurrently.

1. Name:           Michael Sahota 	email: sahota@cs.ubc.ca
   WWW URL:  http://www.cs.ubc.ca/spider/sahota/michael.html
2. Supervisor:     Alan Mackworth	email: mack@cs.ubc.ca
3. Institution:    University of British Columbia
                   Laboratory for Computational Intelligence
4. Research Area:  Computer Vision, Autonomous robots 
5. Summary: 
	I am interested building computer vision systems:
		- using conventional computing technology
		- that respond on the same time scale as human beings 
		- that can accomplish a number of tasks 
	I am currently investigating robust tracking and segmentation
	techniques for fun.  For my PhD, I will probably be building an
	extensive vision system for a robot that can navigate in rough
	terrain.

1. Name:  Rene Schaad    email: schaad@ifi.unizh.ch
          url:   http://josef.ifi.unizh.ch/groups/ailab/people/schaad.html
2. Supervisor: Rolf Pfeifer   email: pfeifer@ifi.unizh.ch
               url:   http://josef.ifi.unizh.ch/groups/ailab/people/pfeifer.html
3. Institution: Artificial Intelligence Laboratory, 
                Departement of Computer Science,
                University of Zurich, Switzerland
4. Research Area: Scaling reinforcement learning to real world domains.
5. Summary:
Reinforcement learning is the method of choice for learning in autonomous
agents. However, RL suffers from severe scaling problems. Multiple goals, large 
input spaces, multiple parallel tasks, and sequentially decomposable tasks 
introduce problems that cannot, in the real world, be solved with monolithic 
architectures.  Our goal is to devise modular architectures that solve the above
scaling problems in real world domains. We draw upon the work of Brooks, Kaelbling, Mahadevan & Connell,
Singh, Whitehead, Thrun, Sutton, Barto, Watkins and others to develop a 
methodological framework for building adaptible autonomous agents. We also
emphasize a principled approach to the action selection problem (Boesser & McFarland, Tyrell).

1. Name:	Peter Scheffel		email: peter@concave.cs.wits.ac.za
2. Supervisor:	Conrad Mueller		email: conrad@concave.cs.wits.ac.za
3. Institution:	University of the Witwatersrand, Johannesburg, SA
4. Research Area:	Path planning for manipulators with DOF<6
5. Summary:
  	
	The aim of the research is to find genrally applicable techniques
	to improve the performance of path planning without precomputing the
	configuration space.  Initially an implementation of an approach
	that does precompute the configuration space was attempted.  This was
	found to have very poor performance especilly on simple cases like
	an empty environment!  The research has therefore concentrated on
	finding solutions to simple problems quickly.  Results achieved so
	for obvious paths in 3 DOF for a 2D env. take under 20 seconds, on a 
	standard 486 PC, with some paths only taking 3 seconds. Most paths 
	can be found in under 10 minutes and memory limitations hinder paths
	that could take more than an hour.  Optimisations have played a
	large part in the feasiblity of the reasearch.  Improvements of the
	order of 5 fold are not uncommon using compulational geometry
	techniques to improve the geometric intersections of lines.

1. Name:          Jeff Schneider   email: schneider@cs.rochester.edu
2. Supervisor:    Chris Brown      email: brown@cs.rochester.edu
3. Institution:   University of Rochester
4. Research Area: Acquisition of Robot Motor Skills
5. Summary:
In open loop skills such as throwing a ball, an entire robot control sequence 
can be viewed as a single point in a high dimensional space.  Then, the problem
of improving accuracy as well as increasing range of performance is a search 
problem.  We have implemented a throwing robot with a flexible link.  We have 
designed an efficient way to search the space with the result that our robot 
learns to "whip" its flexible link at the right frequency to produce long 
throws.  The result is particularly encouraging since the robot was not given 
any model of its flexible link, and no samples of the "whipping" motion were 
ever shown to it.  Recent work considers the acquisition and improvement of 
closed loop skills.  Highly skilled humans have the ability to perform complex 
motions relatively open loop (consider a hockey player that corners in a single 
smooth motion compared to the beginner that must concentrate on balance 
throughout the turn).  We believe that closed loop skill acquisition can benefit
from an attempt to make the skills more open loop as learning progresses.

1. Name:		Todd Sharpe		sharpe@mecad.uta.edu
2. Supervisor:		Dr. Tom J. Lawley	lawley@mecad.uta.edu
3. Institution:		The University of Texas at Arlington
4. Research Areas:	Modular Robotics
5. Summary
Our group is working on producing a modular robot.  The basic idea
is that various link geometries coupled with various motors can
emulate most any present serial robot configuration.  Furthermore,
the modularity allows for upgrades in the future without total 
replacement.  My research deals with developing the quick
connect/disconnect for the modualrity and the motor selection
used in the joints.  A key to this project is that we plan to
implement nural networks as control.  This controler theory tends
to be advantageous to the modular theory.

1. Name:	Gaurav S. Sukhatme email:  gaurav@robotics.usc.edu
	url:   	http://www.usc.edu/dept/robotics/personal/gaurav/home.html
2. Supervisor:	Professor George A. Bekey email:  bekey@cs.usc.edu
	url:	http://www.usc.edu/dept/robotics/personal/bekey/home.html
3. Institution:	Department of Computer Science
		Institute for Robotics and Intelligent Systems
		University of Southern California
4. Research Area: Performance Evaluation of Autonomous Mobile Robots
5. Summary: Performance evaluation and prediction are becoming
increasingly important issues in robotics as the science matures. I am
developing a theoretical framework for the evaluation of highly
autonomous mobile robots. The application area of interest to me is
extraterrestrial exploration. The project I am working on also
involves the application of our theory and evalution methodolgy to two
mobile robots with different modalities of locomotion, namely legs and
wheels.

1. Name:	  Armin Sulzmann  email: sulzmann@imtsg1.epfl.ch
2. Supervisor:	  R.Clavel	  email: 
3. Institution:   Swiss Federal Institute of Technology, Lausanne, Switzerland
4. Research Area: Micro-Robotics
5. Summary:
	This research examines the question: 
	Developement of a vision-based (virtuel-reality) System 
	to guide the manipulations of microsystems, microstructurs, etc.

1. Name:  Narayanan Swaminathan	email:	u64812@uicvm.cc.uic.edu
		url: http://www.me.uic.edu/swami/swami.html
2. Supervisor: Shin-Min Song		
3. Institution:	University of Illinois at Chicago
4. Research Area: Leg design for walking machines
5. Summary: A leg mechanism that provides straight line motion is 
desirable because it doesnt lose energy due to changes in potential 
energy. I am trying to incorporate an ankle mechanism that could do the 
trick.

1. Name:          Hans Tangelder     email:j.w.h.tangelder@io.tudelft.nl
2. Supervisor:    Joris Vergeest
3. Institution:   Delft University of Technology
                  Faculty of Industrial Design Engineering
                  Delft, The Netherlands.
4. Research Area: Rapid Prototyping using Robot Milling

5. Summary:
One of the favourable techniques for rapid shape prototyping is numerically 
controlled milling. For this purpose we have installed a Sculpturing Robot 
work cell consisting of a 6-DOF industrial robot and a turn table on which 
a foam stock is placed. The Sculpturing Robot work cell is driven by an 
off-line generated path file. This path is calculated from the data 
representing the shape, or object, that must be replicated. This path is 
the result of a strategy that must take into account the limits of tool work 
space as well as the shape and placement of all obstacles within this space.
The proposed project aims at finding appropriate methods for such a process. 
They must meet severe requirements concerning safety, autonomy, robustness, 
accuracy, speed and insensitivity to imperfections of the input geometry. 

1. Name:  Geb W. Thomas            email: gwt103@psu.edu
2. Supervisor:  David C. Cannon         email: djcie@engr.psu.edu
3. Institution:  Industrial Engineering, The Pennsylvania State University.
4. Research Area:  Telerobotic interfaces
5. Summary:   We build telerobotic systems that allow the human supervisor 
to direct the robot at the highest level convenient to both 
the robot and human.  We are especially 
interested in directing robots working in unstructured environments performing 
tasks like nuclear waste remediation and small batch manufacturing.  Our 
interfaces combine video information from the remote environment with solid 
models.  I design and build the systems and then focus on how the interfaces 
transmit geometric information to the operator, and the resulting biases and 
inaccuracies in the operator's mental model of the robot's workcell.
Network and graphics programming, experimental design, 
and cognitive analysis are the skills I apply most often.

1. Name: Adrian Thompson      email: adrianth@cogs.susx.ac.uk
                              url: http://www.cogs.susx.ac.uk/users/adrianth/
2. Supervisor: Phil Husbands  email: philh@cogs.susx.ac.uk
               Dave Cliff     email: davec@cogs.susx.ac.uk
                              url: http://www.cogs.susx.ac.uk/users/davec/
3. Institution: COGS, University of Sussex, England
                              url: http://www.cogs.susx.ac.uk/
4. Research Area: Evolutionary Robotics
5. Summary:
Conventional artificial neural network models are not well suited to VLSI
implementation. In Evolutionary Robotics, the control systems for autonomous
mobile robots are artificially evolved, rather than designed. This opens the
possibility of evolving a control system which is optimised for a particular
implementation (such as a Field Programmable Gate Array). Thus, a new kind of
parallel distributed processing system can emerge, which takes advantage of
the characteristics of the hardware and automatically meets any constraints
imposed by it. I am particularly interested in evolving continuous time
systems with complex dynamics, which may help to overcome the connectivity
constraints of VLSI. I have built a robot named "Mr Chips" - see my web page
for details.

1. Name:        Marc Tremblay   
             email: tremblay@cdr.stanford.edu
             URL:   http://cdr.stanford.edu/html/people/tremblay/bio.html
2. Supervisor:  Mark Cutkosky
             email: cutkosky@cdr.stanford.edu
             URL:   http://cdr.stanford.edu/html/people/cutkosky/home.html
3. Institution: Center for Design Research
             Mechanical Engineering Department
             Stanford University
4. Research Area: Tactile sensing and dextrous manipulation
5. Summary: We are studying ways to achieve robust event detection during
         a dextrous manipulation task. The approach utilizes a
         combination of tactile sensors as well as contextual
         information. The manipulation task is decomposed into
         distinct phases, each of which is associated with a limited 
         number of feasible events such as making or breaking contact,
         slipping, etc. A set of context-based and sensor-based
         features is associated with each possible event for each
         type of manipulation phase. The goal is to detect events such
         as finger/object contact or the onset of sliding as robustly
         and as rapidly as possible. At any time during a task, each 
         possible event is assigned a confidence value between 0 and 1
         which indicates the confidence that that particular event 
         could be occurring at that instant. A high-level controller 
         can then make use of this information to determine when to 
         switch to a different manipulation phase.

1. Name:        Eddie Tunstel	email: tunstel@chama.eece.unm.edu
				or     tunstel@robotics.jpl.nasa.gov
2. Supervisor:	Dr. M Jamshidi	email: jamshid@houdini.eece.unm.edu
3. Institution: University of New Mexico, Albuquerque
4. Res Area:	Fuzzy and Intelligent Control of Mobile Robots
5. Summary:
	This research focusses on the development of hybrid intelligent
	control architectures for autonomous mobile robots and mobile
	manipulation.  The work includes investigations of various
	combinations of paradigms such as fuzzy logic, neural networks,
	behavior control, and genetic algorithms for real time motion
	control.  The research focus is on control architectures for
	navigation, path planning, and environment mapping with empahasis
	on embedded application.

1. Name: 	Cem Unsal    	email: unsal@blackbox.cl.ee.vt.edu  
2. Supervisor:	John S. Bay	email: bayj@vtvm1.cc.vt.edu
3. Institution: Virginia Tech, Blacksburg, VA, USA
4. Research Area:  Multiple Mobile Robots (Army-ant Project)
5. Summary: 
My research is based on the idea of using a large homogeneous population of  
mobile robots as a transportation system. Army-ant scenario may also be  
applied to space/underwater missions. We treat "army-ant swarm" as a  
self-organizing system. Robots are simple in terms of knowledge and/or  
communication abilities. Important characteristic of the scenario are: lack  
of map knowledge, large number of agent, non-hiererchical structure,  
emergence (of some form) of intelligence from local interactions and simple  
behavioral rules. 

I'm currently working on behavioral  self-organization (decision systems) of  
multiple agents. 

1.Names:        Torsten Schoenberg email: torstens@automaatio.hut.fi
                Mika Vainio       email: mikav@automaatio.hut.fi
                                         vainio@niksula.hut.fi
2.Supervisor:   Aarne Halme       email: aarneh@aut0maatio.hut.fi
3.Institution:  Automation Laboratory, Helsinki University of 
                Technology, Helsinki, Finland                 
4.Research Area:  Robot Societies: Theory and applications
5.Summary:
Our four member team has been working from the begining of 1992 with 
the Robot Society concept. The first part of the reasearch was to 
define robot society's main structures. Ant societies were 
studied in order to find the key issues, which control ants' 
seemingly chaotic societies. Next phase was to design a model 
society, which is now under construction. It consists of two types of 
autonomous mobile robots(named as the Workers and the Energy-
carriers). The task for the society is a classical one; its job is 
to gather stones from an initially unknown environment along with 
mapping the environment while operating. This society has been 
implemented both as a physical system(still lot of work to be done!) 
and as a simulated one[1-2]. Parallel to this basic research we have 
been looking for a suitable real world application, where some of our 
early results could be verified. Finally from the begining of this 
year we have been building a more realistic robot society. The idea 
is that this society will operate inside a true industrial process. A 
dynamic and hostile 3D world will provide more than adequate number 
of problems to be solved.

[1] Halme A, Jakubik P, Schoenberg T, Vainio M, (1993) "The Concept of 
    Robot Society and Its Utilization," IEEE Int. Workshop on Advanced 
    Robotics.
[2] Halme A, Jakubik P, Schoenberg T, Vainio M, (1994) "The Concept of 
    Robot Society and Its Utilization in Future Robotics," Int. 
    Workshop on Advanced Robotics and Intelligent Machines.

1. Name:        Jim Vaughan         email: jev1@uk.ac.bton.unix     
2. Supervisor:  Graeme Awcock       email: gja@unix.bton.ac.uk
3. Institution: University of Brighton, UK                          
4. Research Area:   Machine vision/sensor fusion
5. Summary:
      Using intelligent sensors, particularly vision, to generate an
      accurate perception of a machine's environment, to allow it to
      operate with a high degree of reliability

1. Name: Virgilio B. Velasco Jr., aka "Dean"  email: vbv@pris.eeap.cwru.edu
2. Supervisor: Wyatt S. Newman                email: wsn@pris.eeap.cwru.edu
3. Institution: Electrical Engineering and Applied Physics Department
		Case Western Reserve University
			AND
		Center for Automation and Intelligent Systems Research
4. Research Area: Agile Manipulation
5. Summary:
	Agile manufacturing is a revolutionary product assembly approach
which allows the manufacturing of a wide variety of products, with selectable
features and batch sizes.  For a robot to do highly agile manufacturing, it
must also be agile in its ability to grasp a wide variety of objects.  This
research project will focus on techniques for grasping and manipulating 
many different objects with a minimal selection of grippers and external
fixtures.  It will also seek to grasp such objects within a minimal amount
of time.

 1. Name:		Richard Voyles		email: robodude@cmu.edu
URL: http://www.cs.cmu.edu:8001/afs/cs.cmu.edu/user/deadslug/ftp/home.html
 2. Supervisor:	Pradeep Khosla		email: pkk@ri.cmu.edu
 3. Institution: 	Carnegie Mellon University, Pittsburgh, PA, USA
URL: http://www.cs.cmu.edu:8001/afs/cs.cmu.edu/user/mwgertz/www/aml.html
 4. Research Area:	Multi-Agent Control/Perception
 5. Summary:
	I'm investigating the cooperation of relatively dumb agents with
	minimal communication channels during control and perception tasks.
	I'm applying systems of encapsulated agents to control of a
	Utah/MIT dextrous hand, control of a Puma 560, and possbily to
	the task of selecting control methodologies for a robot.

1. Name:	   Gabriel D. Warshaw	email: gabriel@sce.carleton.ca
2. Supervisor:	   Howard Schwartz	
3. Institution:    Carleton University, Ottawa, Ontario, Canada
4. Research Area:  Sampled-Data Robot Adaptive Control
5. Summary:
	I am addressing the stability and performance of discretized
adaptive control algorithms for robotic manipulator control, and the
compensation of these algorithms for improved stability and tracking
performance.  The discretization of adaptive control algorithms
published in the literature can result in a sampled-data robot system
for which stability has not been guaranteed.  By formulating the
entire sampled-data system in continuous-time, I have used Lyapunov's
direct method to determine the stability and to derive a non-linear
discrete-time compensating term.  I have demonstrated the theoretical
results through simulation and implementation on a 2 degree-of-freedom
direct drive manipulator.

 1. Name: Martin D. Westhead <martinwe@aifh.ed.ac.uk>
 2. Supervisor: John Hallam
 3. Institution: Dept of Artificial Intelligence, Edinburgh University, UK
 4. Research Area: Theoretical underpinnings of behaviour based systems
 5. Summary:
This work is still in its early stages, but will attempt to apply
formalisms such as process algebra's, dynamical systems and petri nets
to the problem of behaviour based robotic control. The goal of the work
is a better understanding of the parallel interaction of behaviour based
systems with the hope that this might provide the foundation for a more
rigorous design methodology than those currently employed.

1. Name: John Winkler email:furd@iastate.edu
2. Supervisor:  Dr Greg Luecke email:grluecke@iastate.edu
3. Institution:  Iowa State University
4. Research Area:  Optical Based Motion Control, Electro-magnetic force
       generation, Linkages, Kinematics and Human-Robot Force Interaction 
       for Virtual Reality Applications
5. Summary:
Dr. Greg Luecke and John Winkler are developing a magnetic interface system to
apply a general class of inertial, gravitational and interactive forces to the
fingertips of a virtual traveler.   This system uses a combination of robotic
manipulators and electromagnetic actions to couple the user to the manipulator
without any sort of mechanical harness.  This coupling will allow the robot to
follow the motion of the operator's hand during free motion, and will provide a
foundation for the applied forces during constrained movement in the virtual
world.   Position, velocity and force feedback are used to command the gross
motions of the robotic manipulator and the fine motions and forces of the
magnetic interface.
	This magnetic interface has been designed and manufactured and is now
in the tracking and force-feedback testing stage.

 1. Name: Jeremy Wyatt <jeremyw@aifh.ed.ac.uk>
          url: http://www.dai.ed.ac.uk:80/students/jeremyw/
 2. Supervisor: Gillian Hayes and John Hallam
 3. Institution: Dept of Artificial Intelligence, Edinburgh University, UK
 4. Research Area: Learning in Mobile Robots
 5. Summary: I an interested in using learning to help design robot
controllers.  I am working on combining a technique called reinforcement
learning with a behaviour based controller.  Elementary behaviours are
learned separately, and then coordinating behaviours are learned. 
Ultimately the aim is to build a hierarchy of behaviours with several levels.

1. Name:	Gordon Wyeth		email: wyeth@elec.uq.oz.au
2. Supervisor:	Mark Schulz		email: marks@elec.uq.oz.au
3. Institution:	Robotics Laboratory,
		Dept. of Electrical and Computer Engineering,
		University of Queensland,
		Brisbane, Australia.
4. Research Areas:	Artificial Neural Control of a Hunt and Gather Robot,
			Micromice.
5. Summary:

	Hunt and Gather Robot

	The main aim of this project is to produce models of cognitive
	structures that support intelligent behaviour sufficient to allow a
	mobile robot to perform collecting tasks. The project involves the
	construction of a robot dog, CORGI, that retrieves tennis balls
	around the lab. The techniques used to build this robot are similar 
	to those used in behaviour-based robotics, but are based on a neural
	paradigm. The robot's primary sense is a CCD camera that is used to
	locate the tennis balls, sense obstacles and to provide visual cues
	to allow the robot to return to its home position. The artificial
	neural network architecture is based on a combination of
	conventional networks (MLP, SOM) and constructs found in Braitenberg
	vehicles. 

	Micromice

	Micromice are autonomous maze solving robots that are entered in
	competitions to see who can solve the maze and run the fastest path
	in the least time. My Micromice include CUQEE I & II, Australian
	Micromouse Champions. CUQEE III is currently in development and
	should debut at the end of 1994. 

1. Name:	Brian Yamauchi		email: yamauchi@alpha.ces.cwru.edu
		url: ftp://alpha.ces.cwru.edu/pub/agents/yamauchi/yamauchi.html
2. Supervisor:	Randall Beer		email: beer@alpha.ces.cwru.edu
3. Institution: Department of Computer Engineering and Science
		Case Western Reserve University, Cleveland, OH
4. Research Area: Exploration and Spatial Learning in Dynamic Environments
5. Summary:

The goal of my Ph.D. thesis research is to develop techniques that
will allow mobile robots to explore, learn, and navigate in the
presence of unpredictable moving obstacles and dynamic changes in both
the topology and structure of the environment.  I have developed an
exploration and navigation system that combines reactive behaviors for
low-level control with an adaptive place network for spatial learning.
This network consists of place units that use competitive learning for
place recognition along with adaptive connections that learn the
geometric relationships between these places.  This system has been
implemented on a real Nomad 200 mobile robot equipped with sonar,
infrared, and laser range sensors, at the Navy Center for Artificial
Intelligence at the Naval Research Laboratory.

1. Name:		Mark Yim	email: mark@killdeer.stanford.edu
2. Supervisor:		J.C. Latombe	email: latombe@cs.stanford.edu
3. Institution: 	Stanford University, Stanford CA, 94305
4. Research Area:	Reconfigurable Modular Robot Locomotion
5. Summary:
	A dynamically reconfigurable modular robot named Polypod has been
	designed, simulated and partially constructed.  Research is
	being done on unusual statically stable locomotion gaits implemented
	on Polypod, for example, a rolling loop, a moving carpet with many
	feet, slinky locomotion...  Each gait is achieved with a very simple
	behaviour based control scheme.  A taxonomy of locomotion and the
	kinematics of locomotion will be analyzed.

1:  Name:  John-David Yoder (JD)  email: jyoder@twain.helios.nd.edu
    URL:        http://www.nd.edu/NDInfo/Research/sskaar/Home.html
2:  Advisor:    Steven Skaar   email  :    steven.b.skaar.1@nd.edu
3:  Institution:  University of Notre Dame
                  Dept. of Aerospace and Mechanical Engineering
4:  Research Area:   Mobile Robots, Rehab Engineering
5:  Summary:
        A prototype of an automatically guided wheelchair system has
    been developed.  This system provides the basis for my research, which
    involves all three phases (location, path generation, and path tracking)
    of the general navigation problem.  Location is handled using a Kalman
    Filter combining dead-reckoning and visual information.  Highly accurate
    position estimates can be maintained despite a poor kinematic model.
    Path generation is accomplished using a teach-repeat model, and path
    tracking is effected using a standard PID control algorithm in 
    conjunction with a purely geometric means of describing the path and
    the current tracking error.

1. Name:   John S. Zelek    email: zelek@cim.mcgill.ca
2. Supervisor: Martin D. Levine email: levine@cim.mcgill.ca
3. Institution: Centre for Intelligent Machines (CIM), McGill University
4. Research Area: Behavior-based control architecture for robot navigation
5. Summary:
Biological creatures apparently execute many tasks in the world by using a
combination of routine skills, without doing any extensive reasoning. 
Brooks (MIT) has used such behaviors in his subsumption architecture as a 
building block for developing intelligent robots.  This was in sharp contrast 
to the traditional robotics approach in the 1970's when robot processing was 
functionally decomposed into sequential processes of sensing, modelling, 
planning, and acting. The major problems with Brooks' architecture are  its 
scalability  to more difficult tasks which may include reasoning, and the 
limitations imposed by not having an internal model.  The subsumption 
architecture did not have any internal model and thus was prone to possible 
inescapable cyclic behavior. Other researchers (e.g. Arkin:90) have 
incorporated a global planner. However, in this case, the role of the
behavioral architecture has been reduced to a purely reactive one while 
executing  a sequence of linear piecewise path segments. 
The intention of this study is to design an architecture that
allows  the behavioral control strategy to be more flexible, generalizable, and
extendable.  The component dedicated to  behavioral activities should be able
to attempt tasks with or without a reasoning module.  We are investigating 2D
navigational tasks for a mobile robot possessing sonar sensors and a
controllable TV camera mounted on a pan-tilt head.
Experimentation with an implementation of this system will help
determine the tradeoffs and limitations of the architecture in various
contextual settings.

1. Name:	   Yan Zhuang	    email: yzhuang@iris.usc.edu
		   URL: http://iris.usc.edu/home/iris/yzhuang/User.html
2. Supervisor:     Ken Goldberg     email: goldberg@tumbler.usc.edu
3. Inistitution:   University of Sothern California
                   Institute for Robotics and Intelligent Systems
4. Reseach Area:   RISC robotics,
		   grasping and fixturing,
		   stability analysis and
		   CAD modeling and its evaluation
5. Summary:	
		   Developing mathematically rigorous algorithm for
		   RISC robotics and automation



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