Skills, Tactics and Plays for Distributed Multi-robot Control in Adversarial Environments

This work presents a pioneering collaboration between two robot soccer teams from different RoboCup leagues, the Small Size League (SSL) and the Middle Size League (MSL). In the SSL, research is focused on fast-paced and advanced team play for a centrally-controlled multi-robot team. MSL, on the other hand, focuses on controlling a distributed multi-robot team. The goal of cooperation between these two leagues is to apply teamwork techniques from the SSL, which have been researched and improved for years, in the MSL. In particular, the Skills Tactics and Plays (STP) team coordination architecture, developed for centralized multi-robot team, is studied and integrated into the distributed team in order to improve the level of team play. The STP architecture enables more sophisticated team play in the MSL team by providing a framework for team strategy adaptation as a function of the state of the game. Voting-based approaches are proposed to overcome the challenge of adapting the STP architecture to a distributed system. Empirical evaluation of STP in the MSL team shows a significant improvement in offensive game play when distinguishing several offensive game states and applying appropriate offensive plays.

[1]  Luke Hunsberger,et al.  A combinatorial auction for collaborative planning , 2000, Proceedings Fourth International Conference on MultiAgent Systems.

[2]  Milind Tambe,et al.  Building large-scale robot systems: Distributed role assignment in dynamic, uncertain domains , 2003 .

[3]  Takeo Kanade,et al.  Intelligent Autonomous Systems , 1991, Robotics Auton. Syst..

[4]  Manuela M. Veloso,et al.  Opponent-driven planning and execution for pass, attack, and defense in a multi-robot soccer team , 2014, AAMAS.

[5]  Lynne E. Parker Designing control laws for cooperative agent teams , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[6]  H. Kuhn The Hungarian method for the assignment problem , 1955 .

[7]  Daniele Nardi,et al.  Coordination among heterogeneous robotic soccer players , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[8]  Manuela M. Veloso,et al.  OBDD-based Universal Planning: Specifying and Solving Planning Problems for Synchronized Agents in Non-deterministic Domains , 1999, Artificial Intelligence Today.

[9]  Mark H. Overmars,et al.  Coordinated path planning for multiple robots , 1998, Robotics Auton. Syst..

[10]  Rjm Rob Janssen,et al.  Centralized learning and planning : for cognitive robots operating in human domains , 2014 .

[11]  Barry Brumitt,et al.  Dynamic mission planning for multiple mobile robots , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[12]  Alessandro Saffiotti,et al.  Robot task planning using semantic maps , 2008, Robotics Auton. Syst..

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