Potential field based approach for coordinate exploration with a multi-robot team

In this paper we introduce a new distributed algorithm for the exploration of an unknown environment with a team of mobile robots. The objective is to explore the whole environment as fastest as possible. The proposed approach is based on the potential field method. The advantages of using this method are several and well known, but the presence of many local minima does not assure the exploration of the entire environment. Our idea is to preserve these advantages but overcome the problem of local minima by introducing a leader in the team which has a different control law, unaffected by this problem. Furthermore, we consider also the case of several local leaders, dynamically selected on the basis of a hierarchy within the team. Extensive simulations are presented to evaluate the performance of the algorithm. In particular, the results are compared with the exploration obtained by a potential field approach without leaders.

[1]  H. Lau,et al.  Behavioural Approach for Multi-Robot Exploration , 2003 .

[2]  Agostino Martinelli,et al.  Distributed Coverage Control for a Multi-Robot Team in a Non-Convex Environment , 2009 .

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

[4]  Gaurav S. Sukhatme,et al.  Mobile Sensor Network Deployment using Potential Fields : A Distributed , Scalable Solution to the Area Coverage Problem , 2002 .

[5]  G. Swaminathan Robot Motion Planning , 2006 .

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

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

[8]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Autonomous Robot Vehicles.

[9]  Sonal Jain,et al.  Multi-robot forest coverage , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Wolfram Burgard,et al.  Collaborative Multi-Robot Localization , 1999, DAGM-Symposium.

[11]  A WesleyMichael,et al.  An algorithm for planning collision-free paths among polyhedral obstacles , 1979 .

[12]  Elon Rimon,et al.  Spanning-tree based coverage of continuous areas by a mobile robot , 2004, Annals of Mathematics and Artificial Intelligence.

[13]  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).

[14]  Sebastian Thrun,et al.  Exploration in active learning , 1998 .

[15]  Tomás Lozano-Pérez,et al.  An algorithm for planning collision-free paths among polyhedral obstacles , 1979, CACM.

[16]  Wolfram Burgard,et al.  Collaborative Multi-Robot Localization , 1999, DAGM-Symposium.

[17]  Elon Rimon,et al.  Spanning-tree based coverage of continuous areas by a mobile robot , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[18]  Giuseppe Oriolo,et al.  Frontier-Based Probabilistic Strategies for Sensor-Based Exploration , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[19]  Gaurav S. Sukhatme,et al.  Constrained coverage for mobile sensor networks , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[20]  Andreas Birk,et al.  Multi-robot exploration under the constraints of wireless networking , 2007 .

[21]  Howie Choset,et al.  Coverage for robotics – A survey of recent results , 2001, Annals of Mathematics and Artificial Intelligence.