Agent-based robot control design for multi-robot cooperation

This paper presents an agent-based robot control (ARC) architecture. ARC features a flexible real-time control system, which is suitable for multi-robot cooperative tasks. It also provides an efficient platform for building up a multi-robot system consisting of heterogeneous robots. In this paper, an experimental study of this architecture is investigated. A cooperative exploration using two mobile robots will be demonstrated. In this experiment, one robot explores the environment by looking for a color-coded target and the other is responsible for task execution at the target position. While exploring in an unknown environment, the first robot, which is equipped with ultrasonic sensors for exploration, records its position as it sees deployed checkpoints. In a later phase, the second robot plans a path to the target directly using information passed from the first robot and get to the target position in an efficient way.

[1]  Nicola Santoro,et al.  Hard Tasks for Weak Robots: The Role of Common Knowledge in Pattern Formation by Autonomous Mobile Robots , 1999, ISAAC.

[2]  Lynne E. Parker,et al.  Editorial: Advances in Multi-Robot Systems , 2002 .

[3]  Lynne E. Parker,et al.  Guest editorial advances in multirobot systems , 2002, IEEE Trans. Robotics Autom..

[4]  Paul S. Schenker,et al.  CAMPOUT: a control architecture for multirobot planetary outposts , 2000, SPIE Optics East.

[5]  Vijay Kumar,et al.  Distributed Search and Rescue with Robot and Sensor Teams , 2003, FSR.

[6]  S. Shankar Sastry,et al.  Probabilistic pursuit-evasion games: theory, implementation, and experimental evaluation , 2002, IEEE Trans. Robotics Autom..

[7]  Hajime Asama,et al.  Design Of An Autonomous And Distributed Robot System: Actress , 1989, Proceedings. IEEE/RSJ International Workshop on Intelligent Robots and Systems '. (IROS '89) 'The Autonomous Mobile Robots and Its Applications.

[8]  Kai-Tai Song,et al.  Flexible real-time control of home robots using a multi-agent based approach , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[9]  Ronald C. Arkin,et al.  Local navigation strategies for a team of robots , 2003, Robotica.