Safe Multirobot Navigation Within Dynamics Constraints In fast robot soccer games, teams play without any human input, avoiding collisions and obstacles and coordinating action to implement team strategy and tactics.

This paper introduces a refinement of the classical sense-plan-act objective maximization method for setting agent goals, a real-time randomized path planner, a bounded accelerationmotioncontrol system, and a randomized velocity- space search for collision avoidance of multiple moving ro- botic agents. We have found this approach to work well for dynamic and unpredictable domains requiring real-time re- sponse and flexible coordination of multiple agents. First, the approach employs randomized search for objective maximi- zation and motion planning, allowing real-time or any-time performance. Next, a novel cooperative safety algorithm is employed which respects agent dynamics limitations while also preventing collisions with static obstacles or other partici- pating agents. An implementation of our multilayer approach has been tested and validated on real robots, forming the basis for an autonomous robotic soccer team.

[1]  Oliver Brock,et al.  High-speed navigation using the global dynamic window approach , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[2]  Brett Browning,et al.  STP: Skills, tactics, and plays for multi-robot control in adversarial environments , 2005 .

[3]  Daniel Vallejo,et al.  OBPRM: an obstacle-based PRM for 3D workspaces , 1998 .

[4]  Lydia E. Kavraki,et al.  Probabilistic roadmaps for path planning in high-dimensional configuration spaces , 1996, IEEE Trans. Robotics Autom..

[5]  Jean-Claude Latombe,et al.  Robot motion planning , 1991, The Kluwer international series in engineering and computer science.

[6]  Jean-Claude Latombe,et al.  Randomized Kinodynamic Motion Planning with Moving Obstacles , 2002, Int. J. Robotics Res..

[7]  John H. Reif,et al.  Complexity of the mover's problem and generalizations , 1979, 20th Annual Symposium on Foundations of Computer Science (sfcs 1979).

[8]  S. LaValle,et al.  Randomized Kinodynamic Planning , 2001 .

[9]  S. LaValle Rapidly-exploring random trees : a new tool for path planning , 1998 .

[10]  Nancy M. Amato,et al.  A randomized roadmap method for path and manipulation planning , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[11]  Christian Laugier,et al.  Towards real-time global motion planning in a dynamic environment using the NLVO concept , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  P. Fiorini,et al.  Motion planning in dynamic environments using the relative velocity paradigm , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[13]  Robert B. Tilove,et al.  Local obstacle avoidance for mobile robots based on the method of artificial potentials , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[14]  Daniel E. Koditschek,et al.  Exact robot navigation by means of potential functions: Some topological considerations , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[15]  Pekka Isto,et al.  Constructing probabilistic roadmaps with powerful local planning and path optimization , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Manuela M. Veloso,et al.  Real-Time Randomized Path Planning for Robot Navigation , 2002, RoboCup.

[17]  Manuela M. Veloso,et al.  The CMUnited-97 Small Robot Team , 1997, RoboCup.

[18]  Hiroaki Kitano,et al.  RoboCup: The Robot World Cup Initiative , 1997, AGENTS '97.

[19]  Mark H. Overmars,et al.  The Gaussian sampling strategy for probabilistic roadmap planners , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[20]  Emanuele Menegatti,et al.  How a Cooperative Behavior can emerge from a Robot Team , 2004, DARS.

[21]  David Hsu,et al.  The bridge test for sampling narrow passages with probabilistic roadmap planners , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[22]  Minoru Asada,et al.  Dynamic task assignment in a multiagent/multitask environment based on module conflict resolution , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[23]  Ronald C. Arkin,et al.  Motor Schema — Based Mobile Robot Navigation , 1989, Int. J. Robotics Res..

[24]  Lydia E. Kavraki,et al.  Randomized preprocessing of configuration for fast path planning , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[25]  Nils J. Nilsson,et al.  Principles of Artificial Intelligence , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Brett Browning,et al.  Multi-robot team response to a multi-robot opponent team , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[27]  David Ball,et al.  Multi-robot Control in Highly Dynamic, Competitive Environments , 2003, RoboCup.

[28]  Thomas Röfer,et al.  A Behavior Architecture for Autonomous Mobile Robots Based on Potential Fields , 2004, RoboCup.

[29]  Manuela M. Veloso,et al.  Motion Control in Dynamic Multi-Robot Environments , 1999, RoboCup.

[30]  Wolfram Burgard,et al.  The dynamic window approach to collision avoidance , 1997, IEEE Robotics Autom. Mag..

[31]  Anthony Stentz Optimal and Efficient Path Planning for Unknown and Dynamic Environments , 1993 .

[32]  Yoram Koren,et al.  Potential field methods and their inherent limitations for mobile robot navigation , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[33]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[34]  Bernhard Nebel,et al.  http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72569 CS Freiburg: Coordinating Robots for Successful Soccer Playing , 2022 .