Valet parking without a valet

What would it be like if we could give our robot high level commands and it would automatically execute them in a verifiably correct fashion in dynamically changing environments? This work demonstrates a method for generating continuous feedback control inputs that satisfy high-level specifications. Using a collection of continuous local feedback control policies in concert with a synthesized discrete automaton, this paper demonstrates the approach on an Ackermann-steered vehicle that satisfies the command "drive around until you find an empty parking space, then park." The system reacts to changing environmental conditions using only local information, while guaranteeing the correct high level behavior. The local policies consider the vehicle body shape as well as bounds on drive and steering velocities. The discrete automaton that invokes the local policies guarantees executions that satisfy the high-level specification based only on information about the current availability of the nearest parking space. This paper also demonstrates coordination of two vehicles using the approach.

[1]  I.I. Hussein,et al.  Real Time Feedback Control for Nonholonomic Mobile Robots With Obstacles , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[2]  Piergiorgio Bertoli,et al.  MBP: a Model Based Planner , 2001 .

[3]  Christian Laugier,et al.  Autonomous Maneuvers of a Nonholonomic Vehicle , 1997, ISER.

[4]  Hadas Kress-Gazit,et al.  Temporal Logic Motion Planning for Mobile Robots , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[5]  Alfred A. Rizzi.  Hybrid control as a method for robot motion programming , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[6]  Howie Choset,et al.  Composition of local potential functions for global robot control and navigation , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[7]  Hadas Kress-Gazit,et al.  Where's Waldo? Sensor-Based Temporal Logic Motion Planning , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[8]  Daniel E. Koditschek,et al.  Sequential Composition of Dynamically Dexterous Robot Behaviors , 1999, Int. J. Robotics Res..

[9]  Steven M. LaValle,et al.  The sampling-based neighborhood graph: an approach to computing and executing feedback motion strategies , 2004, IEEE Transactions on Robotics and Automation.

[10]  Howie Choset,et al.  Integrated Planning and Control for Convex-bodied Nonholonomic Systems using Local Feedback Control Policies , 2006, Robotics: Science and Systems.

[11]  Amir Pnueli,et al.  Synthesis of Reactive(1) Designs , 2006, VMCAI.

[12]  E. Allen Emerson,et al.  Temporal and Modal Logic , 1991, Handbook of Theoretical Computer Science, Volume B: Formal Models and Sematics.

[13]  George J. Pappas,et al.  Hybrid Controllers for Path Planning: A Temporal Logic Approach , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[14]  Elad Shahar,et al.  The TLV System and its Applications , 1996 .

[15]  Calin Belta,et al.  Discrete abstractions for robot motion planning and control in polygonal environments , 2005, IEEE Transactions on Robotics.

[16]  Antonio Bicchi,et al.  Path tracking control for Dubin's cars , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

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

[18]  Calin Belta,et al.  A Fully Automated Framework for Control of Linear Systems from LTL Specifications , 2006, HSCC.