Just-in-time synthesis for reactive motion planning with temporal logic

The cost of the great expressivity of motion planning subject to temporal logic formulae is intractability. Recent advances in sampling-based methods seem to be only applicable to “low-level” control. The problem of realizing “high-level” controllers that satisfy a temporal logic specification does not readily admit approximations, unless the notion of correctness is relaxed as might be achieved with probabilistic variants of temporal logics. In this paper, we argue that not all possible environment (uncontrolled) behaviors need to be explicitly planned for, but rather short-time strategies can be generated online while maintaining global correctness. We achieve this by separating feasibility from controller synthesis, using metrics from the underlying continuous state space to ensure short-time strategies chained together provide globally correct behavior.

[1]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[2]  Christel Baier,et al.  PROBMELA: a modeling language for communicating probabilistic processes , 2004, Proceedings. Second ACM and IEEE International Conference on Formal Methods and Models for Co-Design, 2004. MEMOCODE '04..

[3]  Emilio Frazzoli,et al.  Sampling-based motion planning with deterministic μ-calculus specifications , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[4]  Calin Belta,et al.  A Fully Automated Framework for Control of Linear Systems from Temporal Logic Specifications , 2008, IEEE Transactions on Automatic Control.

[5]  Hadas Kress-Gazit,et al.  Temporal-Logic-Based Reactive Mission and Motion Planning , 2009, IEEE Transactions on Robotics.

[6]  Paulo Tabuada,et al.  Verification and Control of Hybrid Systems - A Symbolic Approach , 2009 .

[7]  Amir Pnueli,et al.  On the synthesis of a reactive module , 1989, POPL '89.

[8]  George J. Pappas,et al.  Symbolic Planning and Control of Robot Motion Finding the Missing Pieces of Current Methods and Ideas , .

[9]  Paulo Tabuada,et al.  Verification and Control of Hybrid Systems , 2009 .

[10]  Thomas Wilke,et al.  Automata logics, and infinite games: a guide to current research , 2002 .

[11]  Thomas Wilke,et al.  Automata Logics, and Infinite Games , 2002, Lecture Notes in Computer Science.

[12]  Amir Pnueli,et al.  Synthesis of Reactive(1) designs , 2006, J. Comput. Syst. Sci..

[13]  Amir Pnueli,et al.  Bridging the gap between fair simulation and trace inclusion , 2005, Inf. Comput..

[14]  Daniel E. Koditschek,et al.  Exact robot navigation using artificial potential functions , 1992, IEEE Trans. Robotics Autom..

[15]  Jan H. van Schuppen,et al.  A control problem for affine dynamical systems on a full-dimensional polytope , 2004, Autom..

[16]  Antonio Bicchi,et al.  Symbolic planning and control of robot motion [Grand Challenges of Robotics] , 2007, IEEE Robotics & Automation Magazine.

[17]  George J. Pappas,et al.  Discrete abstractions of hybrid systems , 2000, Proceedings of the IEEE.

[18]  Calin Belta,et al.  Receding horizon surveillance with temporal logic specifications , 2010, 49th IEEE Conference on Decision and Control (CDC).

[19]  Ufuk Topcu,et al.  Receding horizon control for temporal logic specifications , 2010, HSCC '10.

[20]  Christel Baier,et al.  Principles of model checking , 2008 .