A cooperative approach for multi-robot area exploration

A cooperation approach with consideration of communication limit is proposed for multi-robot area exploration, in which all the robots select local destinations satisfying the constraints on communication range and reach their destinations at the same time to communicate and fuse their map information. Firstly, the robots compute the frontier between the explored region and the unexplored one. The robots choose the optimal frontier points, which maximize information gain, minimize navigation cost and satisfy communication limit as their local destinations. Then the problem of global exploration in unknown environment is converted into that of multi-stage trajectory planning in local known environment. Collision-free, synchronous and separate trajectories are planned for all the robots to realize the limited communication at their destinations. In such a way, efficient and distributed exploration can be achieved. Simulation results are presented to show the effectiveness of our method.

[1]  Stergios I. Roumeliotis,et al.  Multi-robot SLAM with Unknown Initial Correspondence: The Robot Rendezvous Case , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Vladimir J. Lumelsky,et al.  Decentralized Motion Planning for Multiple Mobile Robots: The Cocktail Party Model , 1997, Auton. Robots.

[3]  Brian Yamauchi,et al.  A frontier-based approach for autonomous exploration , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.

[4]  Kurt Konolige,et al.  A practical, decision-theoretic approach to multi-robot mapping and exploration , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[5]  Gregory Dudek,et al.  Collaborative Robot Exploration and Rendezvous: Algorithms, Performance Bounds and Observations , 2001, Auton. Robots.

[6]  Viii Supervisor.  Sonar-Based Real-World Mapping and Navigation , 2001 .

[7]  Vladimir J. Lumelsky,et al.  Path-planning strategies for a point mobile automaton moving amidst unknown obstacles of arbitrary shape , 1987, Algorithmica.

[8]  Wolfram Burgard,et al.  Collaborative multi-robot exploration , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[9]  Brian Yamauchi,et al.  Frontier-based exploration using multiple robots , 1998, AGENTS '98.

[10]  Wolfram Burgard,et al.  Coordinated multi-robot exploration , 2005, IEEE Transactions on Robotics.

[11]  Michail G. Lagoudakis,et al.  Multi-robot routing under limited communication range , 2008, 2008 IEEE International Conference on Robotics and Automation.

[12]  Massimo Paolucci,et al.  Information-based multi-agent exploration , 2002, Proceedings of the Third International Workshop on Robot Motion and Control, 2002. RoMoCo '02..

[13]  Anthony Stentz,et al.  Multi-robot exploration controlled by a market economy , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[14]  Paolo Fiorini,et al.  Motion Planning in Dynamic Environments Using Velocity Obstacles , 1998, Int. J. Robotics Res..

[15]  Stephen L. Chiu,et al.  Fuzzy Model Identification Based on Cluster Estimation , 1994, J. Intell. Fuzzy Syst..