On the completeness of ensembles of motion planners for decentralized planning

We provide a set of sufficient conditions to establish the completeness of an ensemble of motion planners-that is, a set of loosely-coupled motion planners that produce a unified result. The planners are assumed to divide the total planning problem across some parameter space(s), such as task space, state space, action space, or time. Robotic applications have employed ensembles of planners for decades, although the concept has not been formally unified or analyzed until now. We focus on applications in multi-robot navigation and collision avoidance. We show that individual resolutionor probabilistically-complete planners that meet certain communication criteria constitute a (respectively, resolution- or probabilistically-) complete ensemble of planners. This ensemble of planners, in turn, guarantees that the robots are free of deadlock, livelock, and starvation.

[1]  Robert Griesemer,et al.  Paxos made live: an engineering perspective , 2007, PODC '07.

[2]  Dinesh Manocha,et al.  The Hybrid Reciprocal Velocity Obstacle , 2011, IEEE Transactions on Robotics.

[3]  Ross A. Knepper,et al.  Pedestrian-inspired sampling-based multi-robot collision avoidance , 2012, 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication.

[4]  John G. Harris,et al.  Autonomous cross-country navigation with the ALV , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[5]  Kostas E. Bekris,et al.  Safe distributed motion coordination for second-order systems with different planning cycles , 2012, Int. J. Robotics Res..

[6]  Rodney A. Brooks,et al.  A subdivision algorithm in configuration space for findpath with rotation , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

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

[8]  Gregory Gutin,et al.  Digraphs - theory, algorithms and applications , 2002 .

[9]  Maxim Likhachev,et al.  D*lite , 2002, AAAI/IAAI.

[10]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[11]  John Canny,et al.  The complexity of robot motion planning , 1988 .

[12]  C. Pichot,et al.  A Model-Based , 1991 .

[13]  Jean-Claude Latombe,et al.  Robot Motion Planning: A Distributed Representation Approach , 1991, Int. J. Robotics Res..

[14]  Jean-Claude Latombe,et al.  On the Probabilistic Foundations of Probabilistic Roadmap Planning , 2006, Int. J. Robotics Res..

[15]  Bernhard Nebel,et al.  Integrating Task and Motion Planning Using Semantic Attachments , 2010, Bridging the Gap Between Task and Motion Planning.

[16]  W. Eric L. Grimson,et al.  Handey: A robot system that recognizes, plans, and manipulates , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[17]  Leslie Pack Kaelbling,et al.  Hierarchical Planning in the Now , 2010, Bridging the Gap Between Task and Motion Planning.

[18]  Tomás Lozano-Pérez,et al.  Spatial Planning: A Configuration Space Approach , 1983, IEEE Transactions on Computers.

[19]  Siddhartha S. Srinivasa,et al.  Hierarchical planning architectures for mobile manipulation tasks in indoor environments , 2010, 2010 IEEE International Conference on Robotics and Automation.

[20]  Florent Lamiraux,et al.  Small-space controllability of a walking humanoid robot , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

[21]  Steven M. LaValle,et al.  On the Relationship between Classical Grid Search and Probabilistic Roadmaps , 2004, Int. J. Robotics Res..

[22]  Stuart J. Russell,et al.  Angelic Semantics for High-Level Actions , 2007, ICAPS.

[23]  Arie Shoshani,et al.  System Deadlocks , 1971, CSUR.

[24]  Brian P. Gerkey,et al.  Model-based , Hierarchical Control of a Mobile Manipulation Platform , 2010 .

[25]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.