@journal{keipour_mousaei_jrr21,
  author = {Keipour, Azarakhsh and Mousaei, Mohammadreza and Scherer, Sebastian},
  title = {ALFA: A dataset for UAV fault and anomaly detection},
  journal = {The International Journal of Robotics Research},
  volume = {40},
  number = {2-3},
  pages = {515-520},
  year = {2021},
  tag = {journal},
  doi = {10.1177/0278364920966642},
  url = {https://doi.org/10.1177/0278364920966642},
  eprint = {https://doi.org/10.1177/0278364920966642}
}

 We present a dataset of several fault types in control surfaces of a fixed-wing 
unmanned aerial vehicle (UAV) for use in fault detection and isolation (FDI) and 
anomaly detection (AD) research. Currently, the dataset includes processed data 
for 47 autonomous flights with 23 sudden full engine failure scenarios and 24 
scenarios for 7 other types of sudden control surface (actuator) faults, with a 
total of 66 minutes of flight under normal conditions and 13 minutes of post-fault 
flight time. It additionally includes many hours of raw data of fully autonomous, 
autopilot-assisted and manual flights with tens of fault scenarios. The ground truth 
of the time and type of faults is provided in each scenario to enable evaluation of 
the methods using the dataset. We have also provided the helper tools in several 
programming languages to load and work with the data and to help the evaluation of a 
detection method using the dataset. A set of metrics is proposed to help to compare 
different methods using the dataset. Most of the current fault detection methods are 
evaluated in simulation and, as far as we know, this dataset is the only one providing 
the real flight data with faults in such capacity. We hope it will help advance the 
state of the art in AD or FDI research for autonomous aerial vehicles and mobile robots 
to enhance the safety of autonomous and remote flight operations further. The dataset 
and the provided tools can be accessed from https://doi.org/10.1184/R1/12707963. 

@article{mousaei_icra22vtol,
  title = {VTOL Failure Detection and Recovery by Utilizing Redundancy},
  author = {Mousaei, Mohammadreza and Keipour, Azarakhsh and Geng, Junyi and Scherer, Sebastian},
  journal = {arXiv preprint arXiv:2206.00588},
  year = {2022},
  tag = {conference},
  url = {https://arxiv.org/abs/2206.00588}
}

Offering vertical take-off and landing (VTOL)
capabilities and the ability to travel great distances are crucial
for Urban Air Mobility (UAM) vehicles. These capabilities make
hybrid VTOLs the clear front-runners among UAM platforms.
On the other hand, concerns regarding the safety and
reliability of autonomous aircraft have grown in response to the
recent growth in aerial vehicle usage. As a result, monitoring
the aircraft status to report any failures and recovering to
prevent the loss of control when a failure happens are becoming
increasingly important. Hybrid VTOLs can withstand some de-
gree of actuator failure due to their intrinsic redundancy. Their
aerodynamic performance, design, modeling, and control have
all been addressed in the previous studies. However, research
on their potential fault tolerance is still a less investigated field.
In this workshop, we will present a summary of our work on
aircraft fault detection and the recovery of our hybrid VTOL.
First, we will go over our real-time aircraft-independent system
for detecting actuator failures and abnormal behaviors. Then,
in the context of our custom tiltrotor VTOL aircraft design,
we talk about our optimization-based control allocation system,
which utilizes the vehicle’s configuration redundancy to recover
from different actuation failures. Finally, we explore the ideas
of how these parts can work together to provide a fail-safe
system. We present our simulation and real-life experiments.

@article{mousaei2022design,
  title = {Design, Modeling and Control for a Tilt-rotor VTOL UAV in the Presence of Actuator Failure},
  author = {Mousaei, Mohammadreza and Geng, Junyi and Keipour, Azarakhsh and Bai, Dongwei and Scherer, Sebastian},
  journal = {arXiv preprint arXiv:2205.05533},
  year = {2022},
  tag = {conference},
  url = {https://arxiv.org/abs/2205.05533}
}

Enabling vertical take-off and landing while pro-
viding the ability to fly long ranges opens the door to a wide
range of new real-world aircraft applications while improving
many existing tasks. Tiltrotor vertical take-off and landing
(VTOL) unmanned aerial vehicles (UAVs) are a better choice
than fixed-wing and multirotor aircraft for such applications.
Prior works on these aircraft have addressed the aerodynamic
performance, design, modeling, and control. However, a less ex-
plored area is the study of their potential fault tolerance due to
their inherent redundancy, which allows them to tolerate some
degree of actuation failure. This paper introduces tolerance to
several types of actuator failures in a tiltrotor VTOL aircraft.
We discuss the design and modeling of a custom tiltrotor VTOL
UAV, which is a combination of a fixed-wing aircraft and a
quadrotor with tilting rotors, where the four propellers can
be rotated individually. Then, we analyze the feasible wrench
space the vehicle can generate and design the dynamic control
allocation so that the system can adapt to actuator failures,
benefiting from the configuration redundancy. The proposed
approach is lightweight and is implemented as an extension to
an already-existing flight control stack. Extensive experiments
validate that the system can maintain the controlled flight under
different actuator failures. This work is the first study of the
tiltrotor VTOL’s fault-tolerance that exploits the configuration
redundancy to the best of our knowledge.

@article{keipour_mousaei_icra22detection,
  title = {Detection and Physical Interaction with Deformable Linear Objects},
  author = {Keipour, Azarakhsh and Mousaei, Mohammadreza and Bandari, Maryam and Schaal, Stefan and Scherer, Sebastian},
  journal = {arXiv preprint arXiv:2205.08041},
  year = {2022},
  tag = {conference},
  url = {https://arxiv.org/abs/2205.08041}
}

Deformable linear objects (e.g., cables, ropes, and
threads) commonly appear in our everyday lives. However,
perception of these objects and the study of physical interaction
with them is still a growing area. There have already been
successful methods to model and track deformable linear
objects. However, the number of methods that can automatically
extract the initial conditions in non-trivial situations for these
methods has been limited, and they have been introduced to
the community only recently. On the other hand, while physical
interaction with these objects has been done with ground
manipulators, there have not been any studies on physical
interaction and manipulation of the deformable linear object
with aerial robots.
This workshop describes our recent work on detecting
deformable linear objects, which uses the segmentation output
of the existing methods to provide the initialization required by
the tracking methods automatically. It works with crossings and
can fill the gaps and occlusions in the segmentation and output
the model desirable for physical interaction and simulation.
Then we present our work on using the method for tasks
such as routing and manipulation with the ground and aerial
robots. We discuss our feasibility analysis on extending the
physical interaction with these objects to aerial manipulation
applications.

@article{keipour_mousaei_2020integration,
  title = {Integration of Fully-Actuated Multirotors into Real-World Applications},
  author = {Keipour, Azarakhsh and Mousaei, Mohammadreza and Ashley, Andrew T and Scherer, Sebastian},
  journal = {arXiv preprint arXiv:2011.06666},
  tag = {conference},
  url = {https://arxiv.org/abs/2011.06666},
  year = {2020}
}

The introduction of fully-actuated multirotors has
opened the door to new possibilities and more efficient solutions
to many real-world applications. However, their integration had
been slower than expected, partly due to the need for new tools
to take full advantage of these robots.
As far as we know, all the groups currently working on
the fully-actuated multirotors develop new full-pose (6-D) tools
and methods to use their robots, which is inefficient, time-
consuming, and requires many resources.
We propose a way of bridging the gap between the tools
already available for underactuated robots and the new fully-
actuated vehicles. The approach can extend the existing under-
actuated flight controllers to support the fully-actuated robots,
or enhance the existing fully-actuated controllers to support
existing underactuated flight stacks. We introduce attitude
strategies that work with the underactuated controllers, tools,
planners and remote control interfaces, all while allowing taking
advantage of the full actuation. Moreover, new methods are
proposed that can properly handle the limited lateral thrust
suffered by many fully-actuated UAV designs. The strategies are
lightweight, simple, and allow rapid integration of the available
tools with these new vehicles for the fast development of new
real-world applications.

@inproceedings{keipour_mousaei_icra19,
  author = {Keipour, Azarakhsh and Mousaei, Mohammadreza and Scherer, Sebastian},
  booktitle = {2019 International Conference on Robotics and Automation (ICRA)},
  title = {Automatic Real-time Anomaly Detection for Autonomous Aerial Vehicles},
  year = {2019},
  volume = {},
  number = {},
  pages = {5679-5685},
  tag = {conference},
  doi = {10.1109/ICRA.2019.8794286},
  url = {https://ieeexplore.ieee.org/abstract/document/8794286}
}

The recent increase in the use of aerial vehicles
raises concerns about the safety and reliability of autonomous
operations. There is a growing need for methods to monitor the
status of these aircraft and report any faults and anomalies to
the safety pilot or to the autopilot to deal with the emergency
situation. In this paper, we present a real-time approach using
the Recursive Least Squares method to detect anomalies in the
behavior of an aircraft. The method models the relationship
between correlated input-output pairs online and uses the model
to detect the anomalies. The result is an easy-to-deploy anomaly
detection method that does not assume a specific aircraft model
and can detect many types of faults and anomalies in a wide
range of autonomous aircraft. The experiments on this method
show a precision of 88.23%, recall of 88.23% and 86.36%
accuracy for over 22 flight tests. The other contribution is
providing a new fault detection open dataset for autonomous
aircraft, which contains complete data and the ground truth
for 22 fixed-wing flights with eight different types of mid-flight
actuator failures to help future fault detection research for
aircraft.

@article{jones_mousaei_wm19,
  title = {Automated Analysis, Reporting, and Archiving for Robotic Nondestructive Assay of Holdup Deposits},
  author = {Jones, Heather and Maley, Siri and Yonekawa, Kenji and Mousaei, Mohammadreza and Yesso, J David and Kohanbash, David and Whittaker, William},
  journal = {arXiv preprint arXiv:1901.10795},
  tag = {conference},
  url = {https://arxiv.org/abs/1901.10795},
  year = {2019}
}

To decommission deactivated gaseous diffusion enrichment facilities, miles of contaminated pipe must be
measured. The current method requires thousands of manual measurements, repeated manual data
transcription, and months of manual analysis. The Pipe Crawling Activity Measurement System
(PCAMS), developed by Carnegie Mellon University and in commissioning for use at the DOE
Portsmouth Gaseous Diffusion Enrichment Facility, uses a robot to measure Uranium-235 from inside
pipes and automatically log the data. Radiation measurements, as well as imagery, geometric modeling,
and precise measurement positioning data are digitally transferred to the PCAMS server. On the server,
data can be automatically processed in minutes and summarized for analyst review. Measurement reports
are auto-generated with the push of a button. A database specially-configured to hold heterogeneous data
such as spectra, images, and robot trajectories serves as archive.
This paper outlines the features and design of the PCAMS Post-Processing Software, currently in
commissioning for use at the Portsmouth Gaseous Diffusion Enrichment Facility. The analysis process,
the analyst interface to the system, and the content of auto-generated reports are each described. Example
pipe-interior geometric surface models, illustration of how key report features apply in operational runs,
and user feedback are discussed.

@article{jones_mousaei_wm19robot,
  title = {A robot for nondestructive assay of holdup deposits in gaseous diffusion piping},
  author = {Jones, Heather and Maley, Siri and Mousaei, Mohammadreza and Kohanbash, David and Whittaker, Warren and Teza, James and Zhang, Andrew and Jog, Nikhil and Whittaker, William},
  journal = {arXiv preprint arXiv:1901.10341},
  tag = {conference},
  url = {https://arxiv.org/abs/1901.10341},
  year = {2019}
}

Miles of contaminated pipe must be measured, foot by foot, as part of the decommissioning effort at
deactivated gaseous diffusion enrichment facilities. The current method requires cutting away
asbestos-lined thermal enclosures and performing repeated, elevated operations to manually measure pipe
from the outside. The RadPiper robot, part of the Pipe Crawling Activity Measurement System (PCAMS)
developed by Carnegie Mellon University and commissioned for use at the DOE Portsmouth Gaseous
Diffusion Enrichment Facility, automatically measures U-235 in pipes from the inside. This improves
certainty, increases safety, and greatly reduces measurement time.
The heart of the RadPiper robot is a sodium iodide scintillation detector in an innovative disc-collimated
assembly. By measuring from inside pipes, the robot significantly increases its count rate relative to
external through-pipe measurements. The robot also provides imagery, models interior pipe geometry,
and precisely measures distance in order to localize radiation measurements. Data collected by this system
provides insight into pipe interiors that is simply not possible from exterior measurements, all while
keeping operators safer.
This paper describes the technical details of the PCAMS RadPiper robot. Key features for this robot
include precision distance measurement, in-pipe obstacle detection, ability to transform for two pipe sizes,
and robustness in autonomous operation. Test results demonstrating the robot’s functionality are
presented, including deployment tolerance tests, safeguarding tests, and localization tests. Integrated robot
tests are also shown.

@inproceedings{mousaei_icc17,
  author = {Mousaei, Mohammadreza and Smida, Besma},
  booktitle = {2017 IEEE International Conference on Communications (ICC)},
  title = {Optimizing pilot overhead for ultra-reliable short-packet transmission},
  year = {2017},
  volume = {},
  number = {},
  pages = {1-5},
  tag = {conference},
  doi = {10.1109/ICC.2017.7996416},
  url = {https://ieeexplore.ieee.org/abstract/document/7996416}
}

In this paper we optimize the pilot overhead for
ultra-reliable short-packet transmission and investigate the de-
pendence of this overhead on packet size and error probability. In
particular, we consider a point-to-point communication in which
one sensor sends messages to a central node, or base-station,
over AWGN with Rayleigh fading channel. We formalize the
optimization in terms of approximate achievable rates at a given
block length, pilot length, and error probability. This leads to
more accurate pilot overhead optimization. Simulation results
show that it is important to take into account the packet size
and the error probability when optimizing the pilot overhead.

@inproceedings{mousaei_milcom17,
  author = {Mousaei, Mohammadreza and Soltanalian, Mojtaba and Smida, Besma},
  booktitle = {MILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM)},
  title = {ComSens: Exploiting pilot diversity for pervasive integration of communication and sensing in MIMO-TDD-Frameworks},
  year = {2017},
  volume = {},
  tag = {conference},
  number = {},
  pages = {617-622},
  doi = {10.1109/MILCOM.2017.8170851},
  url = {https://ieeexplore.ieee.org/abstract/document/8170851}
}

In this paper, we propose a fully-integrated radar and communication system - named 
ComSens. We utilize two different pilot sequences (one for uplink and one for downlink) 
with the condition that they must be uncorrelated to each other. Within such a framework, 
the signal received from end-user and the back-scattered signal from the desired objects 
have uncorrelated pilots. Thus, the base-station is able to distinguish data signal from 
user and back-scattered signal from object. We assume a time division duplex (TDD) 
framework. The pilot sequences are designed for MIMO channels. We evaluate channel MSE as 
a figure of merit for communication system. We also show that the designed pilots are 
uncorrelated for a range of time lags. Moreover, designed uplink pilot has negligable 
autocorrelation for a range of time lags leading to an impulse-like autocorrelation 
for radar sensing.

@article{mousaei2019msthesis,
  title = {Efficient Use of Spectral Resources in Wireless Communication Using Training Data Optimization},
  author = {Mousaei, Mohammadreza},
  journal = {arXiv preprint arXiv:1903.12259},
  year = {2019},
  tag = {msthesis},
  url = {https://arxiv.org/abs/1903.12259}
}

Wireless communication applications has acquired a vastly increasing range over the past decade.
This rapidly increasing demand implies limitations on utilizing wireless resources. One of the most
important resources in wireless communication is frequency spectrum. This thesis provides different
solutions towards increasing the spectral efficiency. The first solution provided in this thesis is to use
a more accurate optimization metric: maximal acheivable rate (compared to traditional metric: ergodic
capacity) to optimize training data size in wireless communication. Training data symbols are previously
known symbols to the receiver inserted in data packets which are used by receiver to acquire channel
state information (CSI). Optimizing training data size with respect to our proposed tight optimization
metric, we could achieve higher rates especially for short packet and ultra reliable applications. Our
second proposed solution to increase spectral efficiency is to design a multifunction communication
and sensing platform utilizing a special training sequence design. We proposed a platform where two
training sequences are designed, one for the base-station and the other for the user. By designing these
two training sequence such that they are uncorrelated to each other, the base station will be able to
distinguish between the two training sequence. Having one of the sequences especially designed for
radar purposes (by designing it such that it has an impulse-like autocorrelation), the system will be able
to sense the environment, transmit and receive the communication data simultaneously.