An Autonomous Exploration Strategy for Cooperative Mobile Robots

DOI: 10.4236/jsea.2014.73016   PDF   HTML     2,754 Downloads   3,831 Views   Citations


Frontier-based exploration methods are efficient for multi-robot exploration systems. In this paper, enhanced frontier-based techniques are used with team of cooperating mobile robots to explore unknown environment. The aim of the exploration algorithm is to minimize the exploration time by coordinating the robots to maximize overall utility by minimizing the potential of overlapping in information gained amongst the robots. The proposed frontier-based exploration algorithm is based on a new bidding function to decrease the overlap between the robots in addition to the utility and cost parameters. A special parameter depends on the future positions of the robots is also considered. The proposed algorithm has been tested with different environments. We also compared it to A* algorithm. Comparisons demonstrated the efficiency of proposed algorithm.

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Al Khawaldah, M. , Al-Khedher, M. , Al-Adwan, I. and Al Rawashdeh, A. (2014) An Autonomous Exploration Strategy for Cooperative Mobile Robots. Journal of Software Engineering and Applications, 7, 142-149. doi: 10.4236/jsea.2014.73016.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Dave, R.N. (1991) Characterization and Detection of Noise in Clustering. Pattern Recognition Letters, 12, 657-664.
[2] Matia, F. and Jimenez, A. (1998) Multisensor Fusion: An Autonomous Mobile Robot. Journal of Intelligent and Robotic Systems, 22, 129-141.
[3] Zelinsky, A. (1991) Mobile Robot Map Making Using Sonar. Journal of Robotic Systems, 8, 557-577.
[4] Simmons, R., Apfelbaum, D., Burgard, W., Fox, D., Thrun, S. and Younes, H. (2000) Coordination for Multi-Robot Exploration and Mapping. Proceedings of the 17th National Conference on Artificial Intelligence and 12th Conference on Innovative Applications of Artificial Intelligence, Austin, 30 July-3 August 2000, 852-858.
[5] Burgard, W., Moors, M., Stachniss, C. and Schneider, F. (2005) Coordinated Multirobot Exploration. IEEE Transactions on Robotics, 21, 376-378.
[6] Yamauchi, B., et al. (1998) Frontier-Based Exploration Using Multiple Robots. Proceedings of the 2nd International Conference on Autonomous Agents, Minneapolis, 10-13 May 1998, 47-53.
[7] Cao, Y.U., Fukunaga, A.S., Kahng, A. and Meng, F. (1997) Cooperative Mobile Robotics: Antecedents and Directions. Autonomous Robots, Pittsburgh, 5-9 August 1995, 7-27.
[8] Burgard, W., Fox, D., Moors, M., Simmons, R. and Thrun, S. (2000) Collaborative Multi-Robot Exploration. IEEE International Conference on Robotics and Automation, 1, 476-481.
[9] Sheng, W., Yang, Q., Tan, J. and Xi, N. (2006) Distributed Multi-Robot Coordination in Area Exploration. Robotics and Autonomous Systems, 54, 945-955. 2006.06.003
[10] Rocha, R., Dias, J. and Carvalho, A. (2005) Cooperative Multi-Robot Systems: A Study of Vision-Based 3-D Mapping Using Information Theory. Robotics and Autonomous Systems, 53, 282-311.
[11] Fox, D., Ko, J., Konolige, K., Limketkai, B., Schulz, D. and Stewart, B. (2006) Distributed Multi-Robot Exploration and Mapping. Proceedings of the IEEE, 94, 1325-1339. 2006.876927
[12] Wilensky, U., NetLogo (1999) Center for Connected Learning and Computer-Based Modeling, Northwestern University. Evanston, IL.
[13] Russell, S.J. and Norvig, P. (2003) Artificial Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River, 97-104.

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