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I. Intro (Text: pdf/ps, (last updated 10/8/2001, Copyright Howie Choset, 2001)
- Where am I?--Sensors and Methods for Mobile Robot Positioning by J. Borenstein , H. R. Everett , and L. Feng
- Robot Motion Planning by J.C. Latombe (out of print)
- Introduction to AI Robotics by Robin Murphy
- Sensors for Mobile Robots by H. Bart R. Everett
- Computational Principles of Mobile Robotics by Gregory Dudek and Michael Jenkin
- Computational Geometry: Algorithms and Applications by Mark de Berg, Marc van Kreveld, Mark Overmars, Otfried Schwarzkopf
- Computational Geometry in C (Second Edition) by Joseph O'Rourke
- A. Bug2
- Lumelsky
- 1. Completeness
- 2. Wall Following: Numeric Continuation Methods
- 3. Centerline Sonar Model: distance to closest obstacle
- 4. Does the robot really reach the goal?
- D. Fox, W. Burgard, and S. Thrun
- Lumelsky
- B. TanBug (Rimon)
- C. Brief Mention of other bugs
- WedgeBug (Laubach & Burdick)
- 3D Bug (Rimon)
- D. Attractive/Repulsive Functions
- 1. Positive Charge Analogy and Hill Climbing
- 2. Potential Function Definition
- 3. Gradient Descent (Minima, maxima, saddle)
- 4. Relate to Direct Sensor Measurements
- 5. Vectorfield Histogram (Borenstein)
- 6. Brushfire
- 7. Fast March Algorithm (Sethian (Potential based))
- E. Local Minimum Problem -- trapped
- F. Navigation Functions (Rimon & Kodicheck)
- G. Principle of Optimality
- H. Randomized Potentials??? (Here or probabilistic techniques chap) (Barraquand, Langlois & Latombe)
- A. Brushfire
- B. Wavefront
- C. Graph Search
- Breadth first search
- Depth first search
- Greedy Search
- D. A* Search
- E. D* Search (Stentz)
- F. Frontier Exploration
- G. Maybe Borenstein here....? (Borenstein)
- A. Configuration Space (Lozano-Perez)
- B. Polygonal Obstacles (De Berg etc. Chapter 13)
- C. Some higher dims
- A. Visibility Graph
- B. Canny's Roadmap (Canny)
- C. OPP
- 1. Canny & Lin
- 2. Rimon
- D. GVG
- E. Place Maps
- A. Probability Primer (Howie wrote this)
- B. Probabilistic potential functions (??? here or above) (Latombe)
- C. Roadmaps
- D. RRT's
- A. Probability Primer (Howie ps/pdf (under serious construction))
- B. Occupancy
- C. Hybrid Approaches
- Thrun
- Kortenkamp
- Arras - (finding line segments from collections of points like Hough)
- A. Kalman
- Text that Howie wrote ps/pdf (under serious construction)
- Davison (slam using vision)
- Leonard and Durrante-Whyte
- Guivant (slam - ekf)
- B. Bayesian
- C. Topological Localization
- D. Particle Filter Techniques (Isard Condenstation algorithm for vision)
- Where? (Deans (Invariant Filter))
- A. Trapezoid (Chazzelle or basic thing)
- B. Boustrophedon and Related Approaches
- C. Approximate Cell Decomposition - Pixel based
- Zelinsky and Yuta
- Rimon
- D. Cellular Decompomposition (Collins - (no papers))
- Arras - (laser and visual homing)
- (restrict to R^n, leave out Lie groups, coordinate-free formalisms, appendix?)
- tangent vector, tangent space, tangent bundle
- vector fields, integral curves, Lie bracket
- distributions, involutivity, integral manifold, Frobenius
- dynamical polysystem, control affine systems, drift and drift-free
- controllability definitions
- Lie algebra of vector fields, LARC
- STLC
- nonholonomic constraints: (Pfaffian) rolling, conservation of momentum
- positive formulation: vector fields; negative: constraints
- underactuated robots (2nd order constraints)
- - motion planning for cars, cars and trailers (Latombe, Laumond, Lumelsky IROS 2000, lots...)
- - holonomic planning followed by transform for STLC systems
- - optimization approaches, nonsingular loops (Wen, Sontag, Sussmann, Fernandes, others)
- - geometric phase, iterative closed loops
- - RRT
- - differentially flat systems (Murray, Fliess, Martin, others)
- - chained form systems (many)
- - kinematically controllable systems (Bullo and Lynch)
- - averaging/oscillatory approaches
- (- mixed kinematic and dynamic)
- - fictitious inputs, Lafferiere's method
- some other references: Latombe book, Canny and Li book, Murray book, Mason book, Wen article, my ME 495 lectures
- path + time-scaling = trajectory
- robot dynamics
- fully actuated vs. underactuated (more on underactuated next chapter)
- kinodynamic (Canny, Donald, Reif, Xavier...)
- RRT (LaValle and Kuffner)
- decoupled approach: path planning followed by time-scaling (Bobrow et al., Shin and McKay, Shiller, Hollerbach, ...)
- optimization approaches (Tan and Potts, Vukobratovic, many using SQP like Bobrow)
- (Lots possible here: need to define scope; below is very rough)
- adding manipulation mechanics to planning
- manipulation taxonomy (Mason and Lynch)
- movable objects (Wilfong)
- transit paths and transfer paths (Alami, Dacre-Wright, Koga, Kuffner, Ferbach ...)
- assembly/disassembly planning, NDBG's, etc. (Wilson, many)
- friction, wrenches, moment labels, form and force closure
- grasp planning (including 2nd order mobility, Rimon and Burdick)
- (possibly finger gaiting, Rus-Zefran-Goodwine etc., rolling, but don't digress into control)
- push planning and controllability of manipulation (Lynch)
- other push planning (Sudsang and Ponce, Agarwal)
- grasp sequences (Brost, Goldberg), conveyor feeding
- LMT
- AND/OR graphs
- Sensors
II. Start-to-Goal Algorithm (Text: pdf/ps, last updated 10/8/2001, Copyright Howie Choset, 2001)
III. Grid and Graph-based Approachess (Text: pdf/ps, last updated 9/25/2001, Copyright Howie Choset, 2001)
IV. Configuration Space (Text: pdf/ps, last updated 11/01/2001, Copyright Howie Choset, 2001)
V. Roadmaps (Text: pdf/ps, last updated 10/10/2001, Copyright Howie Choset, 2001)
VI. Probabilistic Motion Planning Techniques
VII. Probabilistic Pixel-Based Maps
VIII. Simultaneous Localization and Mapping
IX. Visibility Based (maybe we will skip)
X. Coverage (Cell Decompositions)
XI. Visual Exploration
XII. Nonholonomic motion planning
XIII. Trajectory planning
XIV. Manipulation planning
XV. Miscellaneous