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Home Page for Ali-akbar Agha-mohammadi | Parasol Laboratory


Picture Ali-akbar Agha-mohammadi
PhD Student
Algorithms & Applications Group

Parasol Laboratory url: http://parasol.tamu.edu/~ali/
Department of Computer Science and Engineering email:
Texas A&M University office: HRBB
College Station, TX 77843-3112 tel:
USA fax: (979) 458-0718


CV/Resume   Publications

I defended my PhD dissertation in 2013 and joined the Laboratory for Information and Decision Systems (LIDS) at MIT as a postdoctoral research associate (see my new home page). In Texas A&M, I was affiliated with the Dynamics & Control Research Group (Dept. of Aerospace Eng.) and Parasol lab (Dept. of Computer Science and Eng.). Co-chairs of my PhD committee were Dr. Suman Chakravorty (Dept. of Aerospace) and Dr. Nancy Amato (Dept. of CSE). In A&M, I worked on estimation, filtering, and control theory with a focus on the problem of planning under uncertainty for robotic systems with imperfect measurements.


Motion Planning Under Uncertainty
The objective of our research is to present feedback-based information roadmap (FIRM), a multi-query approach for planning under uncertainty which is a belief-space variant of probabilistic roadmap methods. The crucial feature of FIRM is that the costs associated with the edges are independent of each other, and in this sense it is the first method that generates a graph in belief space that preserves the optimal substructure property. From a practical point of view, FIRM is a robust and reliable planning framework. It is robust since the solution is a feedback and there is no need for expensive replanning. It is reliable because accurate collision probabilities can be computed along the edges. In addition, FIRM is a scalable framework, where the complexity of planning with FIRM is a constant multiplier of the complexity of planning with PRM. FIRM is developed as an abstract framework. As a concrete instantiation of FIRM, we can adopt different belief stabilizers. For example, utilizing stationary linear quadratic Gaussian (SLQG) controllers as belief stabilizers, we introduce the so-called SLQG-FIRM.


Recent Refereed Publications

FIRM: Sampling-based Feedback Motion Planning Under Motion Uncertainty and Imperfect Measurements, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, International Journal of Robotics Research (IJRR), To appear.
Journal(pdf, abstract)

Motion Planning under Uncertainty, Ali-akbar Agha-mohammadi, Sandip Kumar, Suman Chakravorty, Book Chapter, J. Valasek (Ed.), Advances in Intelligent and Autonomous Aerospace Systems, Progress in Astronautics and Aeronautics, American Institute of Aeronautics and Astronautics (AIAA), Reston, VA, 2012.

Graph-based Stochastic Control with Constraints: A Unified Approach with Perfect and Imperfect Measurements, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, In American Control Conference (ACC'13), invited session on Stochastic Models, Control and Algorithms in Robotics, Washington, DC, Jun 2013.
Proceedings(pdf, abstract)

Sampling-based Nonholonomic Motion Planning in Belief Space via Dynamic Feedback Linearization-based FIRM, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, In Proc. IEEE Int. Conf. Intel. Rob. Syst. (IROS'12), Vilamoura, Portugal, Oct 2012.
Proceedings(pdf, abstract)

On the Probabilistic Completeness of the Sampling-based Feedback Motion Planners in Belief Space, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, In Proc. IEEE Int. Conf. Robot. Autom. (ICRA'12), Saint Paul, Minnesota, May 2012.
Proceedings(pdf, abstract)

FIRM: Feedback Controller-Based Information-State Roadmap -- A Framework for Motion Planning Under Uncertainty --, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, In Proc. IEEE Int. Conf. Intel. Rob. Syst. (IROS'11), San Francisco, CA, Sep 2011.
Proceedings(pdf, abstract)

Robust Recognition of Planar Mirrored Walls Using a Single View, Ali-akbar Agha-mohammadi, Dezhen Song, IEEE International Conference on Robotics and Automation (ICRA'11), Shanghai, China, 2011.
Proceedings(pdf)

On the Consistency of EKF-SLAM:Focusing on the Observation Models, Amir-hossein Tamjidi, Hamid D. Taghirad, Ali-akbar Agha-mohammadi, IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS'09), St. Louis, US, 2009.

A Solution for SLAM through Augmenting Vision and Range Information, Ali-akbar Agha-mohammadi, Amir-hossein Tamjidi, Hamid D. Taghirad IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS'08), Nice, France, 2008.

SLAM Based On the LRF Information as the Only Data Source, Ali-akbar Agha-mohammadi, Amir-hossein Tamjidi, Hamid D. Taghirad Proc. of the 17th International Federation of Automatic Control, (IFAC'08), Seoul, Korea, 2008.

Feature-Based Range Scan Matching For Accurate and High Speed Mobile Robot Localization, Ali-akbar Agha-mohammadi, Hamid D. Taghirad, Amir-hossein Tamjidi, Ehsan Mihankhah InProc. of Third European Conference on Mobile Robots (ECMR'07), Freiburg, Germany, pp.253-258, 2007.

Workshop Papers, Posters, and Technical Reports

Online Replanning in Belief Space for Dynamical Systems: Towards Handling Discrete Changes of Goal Location, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, In IEEE ICRA 2013 Workshop on Combining Task and Motion Planning, Karlsruhe, Germany, May 2013.
Proceedings(pdf, abstract)

Medical Needle Steering under Motion and Sensor Noise using Feedback-based Information Roadmaps, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, In IEEE ICRA 2012 Needle Steering Workshop, Saint Paul, Minnesota, May 2012. (pdf)

Dynamic Real-time Replanning in Belief Space: An Experimental Study on Physical Mobile Robots, Ali-akbar Agha-mohammadi, Saurav Agarwal, Aditya Mahadevan, Suman Chakravorty, Daniel Tomkins, Jory Denny, Nancy M. Amato, Technical Report, TR13-007, Parasol Laboratory, Department of Computer Science, Texas A&M University, Jul 2013.
Technical Report(pdf, abstract)

Sampling-based Nonholonomic Motion Planning in Belief Space via Dynamic Feedback Linearization-based FIRM, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, Technical Report, TR12-004, Parasol Laboratory, Department of Computer Science, Texas A&M University, Mar 2012.
Technical Report(pdf, abstract)

Periodic-Feedback Motion Planning in Belief Space for Nonholonomic and/or Nonstoppable Robots, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, Technical Report, TR12-003, Parasol Laboratory, Department of Computer Science, Texas A&M University, Feb 2012.
Technical Report(pdf, abstract)

Sampling-based Feedback Motion Planning Under Motion Uncertainty and Imperfect Measurements, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, Technical Report, TR11-007, Parasol Laboratory, Department of Computer Science, Texas A&M University, Dec 2011.
Technical Report(pdf, abstract)

On the Probabilistic Completeness of the Sampling-based Feedback Motion Planners in Belief Space, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato, Technical Report, TR11-006, Parasol Laboratory, Department of Computer Science, Texas A&M University, Nov 2011.
Technical Report(pdf, abstract)

FIRM: Feedback Controller-Based Information-State Roadmap, A Framework for Motion Planning Under Uncertainty, Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy Amato, Technical Report, TR11-001, Parasol Laboratory, Department of Computer Science, Texas A&M University, Jan 2011.
Technical Report(pdf, abstract)

Resquake, A Tracked Mobile Rescue Robot, Arash Kalantari, Ehsan Mihankhah, Ali-akbar Agha-mohammadi, Rescue Robotics Camp, IEEE International Workshop on Safety Security and Rescue Robotics (SSRR'07), Rome, Italy, 2007.