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Publications of year 2001

Thesis

  1. E. Frazzoli. Robust Hybrid Control for Autonomous Vehicle Motion Planning. Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, June 2001. [PDF] Keyword(s): Motion Planning, Robotics, Hybrid Systems, Quantized Control.

    This dissertation focuses on the problem of motion planning for agile autonomous vehicles. In realistic situations, the motion planning problem must be solved in real-time, in a dynamic and uncertain environment. The fulfillment of the mission objectives might also require the exploitation of the full maneuvering capabilities of the vehicle. The main contribution of the dissertation is the development of a new computational and modelling framework (the Maneuver Automaton), and related algorithms, for steering underactuated, nonholonomic mechanical systems. The proposed approach is based on a quantization of the system's dynamics, by which the feasible nominal system trajectories are restricted to the family of curvesthat can be obtained by the interconnection of suitably defined primitives. This can be seen as a formalization of the concept of {\em maneuver}, allowing for the construction of a framework amenable to mathematical programming. This motion planning framework is applicable to all time-invariant dynamical systems which admit dynamic symmetries and relative equilibria. No other assumptions are made on the dynamics, thus resulting in exact motion planning techniques of general applicability. Building on a relatively expensive off-line computation phase, we provide algorithms viable for real-time applications. A fundamental advantage of this approach is the ability to provide a mathematical foundation for generating a provably stable and consistent hierarchical system, and for developing the tools to analyze the robustness of the system in the presence of uncertainty and/or disturbances. In the second part of the dissertation, a randomized algorithm is proposed for real-time motion planning in a dynamic environment. By employing the optimal control solution in a free space developed for the maneuver automaton (or for any other general system), we present a motion planning algorithm with probabilistic convergence and performance guarantees, and hard safety guarantees, even in the face of finite computation times. The proposed methodologies are applicable to a very large class of autonomous vehicles: throughout the dissertation, examples, simulation and experimental results are presented and discussed, involving a variety of mechanical systems, ranging from simple academic examples and laboratory setups, to detailed models of small autonomous helicopters.


  2. @phdthesis{Frazzoli:PhD01,
    Abstract = {This dissertation focuses on the problem of motion planning for agile autonomous vehicles. In realistic situations, the motion planning problem must be solved in real-time, in a dynamic and uncertain environment. The fulfillment of the mission objectives might also require the exploitation of the full maneuvering capabilities of the vehicle. The main contribution of the dissertation is the development of a new computational and modelling framework (the Maneuver Automaton), and related algorithms, for steering underactuated, nonholonomic mechanical systems. The proposed approach is based on a quantization of the system's dynamics, by which the feasible nominal system trajectories are restricted to the family of curvesthat can be obtained by the interconnection of suitably defined primitives. This can be seen as a formalization of the concept of {\em maneuver}, allowing for the construction of a framework amenable to mathematical programming. This motion planning framework is applicable to all time-invariant dynamical systems which admit dynamic symmetries and relative equilibria. No other assumptions are made on the dynamics, thus resulting in exact motion planning techniques of general applicability. Building on a relatively expensive off-line computation phase, we provide algorithms viable for real-time applications. A fundamental advantage of this approach is the ability to provide a mathematical foundation for generating a provably stable and consistent hierarchical system, and for developing the tools to analyze the robustness of the system in the presence of uncertainty and/or disturbances. In the second part of the dissertation, a randomized algorithm is proposed for real-time motion planning in a dynamic environment. By employing the optimal control solution in a free space developed for the maneuver automaton (or for any other general system), we present a motion planning algorithm with probabilistic convergence and performance guarantees, and hard safety guarantees, even in the face of finite computation times. The proposed methodologies are applicable to a very large class of autonomous vehicles: throughout the dissertation, examples, simulation and experimental results are presented and discussed, involving a variety of mechanical systems, ranging from simple academic examples and laboratory setups, to detailed models of small autonomous helicopters. },
    Address = {Cambridge, MA},
    Author = {E. Frazzoli},
    Date-Modified = {2010-02-21 06:38:13 -0800},
    Keywords = {Motion Planning, Robotics, Hybrid Systems, Quantized Control},
    Local-Url = {/www/papers/Frazzoli.PhD01.pdf},
    Month = {June},
    Pdf = {http://ares.lids.mit.edu/papers/Frazzoli.PhD01.pdf},
    School = {Massachusetts Institute of Technology},
    Title = {Robust Hybrid Control for Autonomous Vehicle Motion Planning},
    Type = {Department of Aeronautics and Astronautics},
    Year = {2001},
    Bdsk-File-1 = {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}
    }
    

Articles in journal, book chapters

  1. E. Frazzoli, Z. H. Mao, J. H. Oh, and E. Feron. Aircraft Conflict Resolution Via Semi-Definite Programming. AIAA J. of Guidance, Control, and Dynamics, 24(1):79-86, 2001. Keyword(s): Air Traffic Control.
    @article{Frazzoli.Mao.ea:01,
    Author = {E. Frazzoli and Z.~H. Mao and J.~H. Oh and E. Feron},
    Date-Modified = {2007-10-20 21:06:11 -0400},
    Journal = {AIAA J. of Guidance, Control, and Dynamics},
    Keywords = {Air Traffic Control},
    Number = {1},
    Pages = {79--86},
    Title = {Aircraft Conflict Resolution Via Semi-Definite Programming},
    Volume = {24},
    Year = {2001}
    }
    

  2. V. Gavrilets, E. Frazzoli, B. Mettler, M. Piedmonte, and E. Feron. Aggressive Maneuvering of Small Autonomous Helicopters: A Human-Centered Approach. International Journal of Robotics Research, 20(10):795-807, 2001. [PDF] Keyword(s): Flight Control.
    @article{Gavrilets.Frazzoli.ea:01,
    Author = {V. Gavrilets and E. Frazzoli and B. Mettler and M. Piedmonte and E. Feron},
    Date-Modified = {2009-03-02 14:29:32 -0500},
    Journal = {International Journal of Robotics Research},
    Keywords = {Flight Control},
    Number = {10},
    Pages = {795--807},
    Pdf = {/papers/Gavrilets.Frazzoli.ea.IJRR01.pdf},
    Title = {Aggressive Maneuvering of Small Autonomous Helicopters: A Human-Centered Approach},
    Volume = {20},
    Year = {2001}
    }
    

Conference articles

  1. E. Frazzoli, M.A. Dahleh, and E. Feron. Real-time motion planning for agile autonomous vehicles. In Proc. American Control Conf., volume 1, pages 43-49, 2001.
    @conference{Frazzoli.Dahleh.ea:ACC01,
    Author = {E. Frazzoli and M.A. Dahleh and E. Feron},
    Booktitle = {Proc. American Control Conf.},
    Date-Added = {2011-01-19 22:37:31 -0500},
    Date-Modified = {2011-01-19 22:38:19 -0500},
    Pages = {43--49},
    Title = {Real-time motion planning for agile autonomous vehicles},
    Volume = {1},
    Year = {2001}
    }
    

  2. E. Frazzoli, M.A. Dahleh, E. Feron, and R.P. Kornfeld. A Randomized Attitude Slew Planning Algorithm for Autonomous Spacecraft. In AIAA Conf. on Guidance, Navigation and Control, Montreal, Canada., 2001.
    @conference{Frazzoli.Dahleh.ea:GNC01,
    Address = {Montreal, Canada.},
    Author = {E. Frazzoli and M.A.~Dahleh and E. Feron and R.P.~Kornfeld},
    Booktitle = {AIAA Conf. on Guidance, Navigation and Control},
    Date-Added = {2009-02-05 00:58:15 -0500},
    Date-Modified = {2009-02-05 00:59:48 -0500},
    Title = {A Randomized Attitude Slew Planning Algorithm for Autonomous Spacecraft},
    Year = {2001}
    }
    


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Last modified: Tue Aug 18 08:30:35 2015
Author: frazzoli.


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