JRM Vol.21 No.1 pp. 44-56
doi: 10.20965/jrm.2009.p0044


Iterative Transportation by Multiple Mobile Robots Considering Unknown Obstacles

Kousuke Inoue*, Jun Ota**, and Tamio Arai**

*Department of Intelligent Systems Engineering, Faculty of Engineering, Ibaraki University

**Department of Precision Engineering, Graduate School of Engineering, The University of Tokyo

March 3, 2008
September 7, 2008
February 20, 2009
multiple mobile robot system, motion planning, cooperative exploration, transportation, learning
The focus in this paper is on a planning method for an iterative transportation task performed by mobile robots in environments including unknown obstacles. This task requires the acquisition of environmental information, the generation of the appropriate path network based on the acquired information, and the formation of a group of robots on the planned path network. To achieve an efficient method of transportation, a motion planning architecture is proposed that includes three phases, i.e., environmental exploration, path generation, and learning of formation. In the first phase, robots cooperatively explore the environment using a learned visibility graph while transporting. Next, a network of transportation paths consisting of 1- and 2-lane paths is generated using two kinds of configuration spaces. In the final phase, every robot learns a behavior strategy by reinforcement learning to acquire an efficient formation of transportation. The simulation results indicate the effectiveness of the proposed architecture.
Cite this article as:
K. Inoue, J. Ota, and T. Arai, “Iterative Transportation by Multiple Mobile Robots Considering Unknown Obstacles,” J. Robot. Mechatron., Vol.21 No.1, pp. 44-56, 2009.
Data files:
  1. [1] J. Ota, “Multi-agent robot systems as distributed autonomous systems,” Advanced Engineering Informatics, Vol.20, pp. 59-70, 2006.
  2. [2] T. Arai and J. Ota, “Motion planning of multiple mobile robots using virtual impedance,” J. Robotics Mechatronics, Vol.8, No.1, pp. 67-74, 1996.
  3. [3] A. Yamashita, T. Arai, J. Ota, and H. Asama, “Motion planning of multiple mobile robots for cooperative manipulation and transportation,” IEEE Trans. Robotics Automat., Vol.19, No.2, pp. 223-237, 2003.
  4. [4] J. Fredslund and M. J. Mataric, “A general algorithm for robot formations using local sensing and minimal communication,” IEEE Trans. Robotics Automat., Vol.18, No.5, pp. 837-846, 2002.
  5. [5] Y. Yoshimura, Jun Ota, K. Inoue, D. Kurabayashi, and T. Arai, “Iterative Transportation planning of multiple objects by cooperative mobile robots,” Distributed Autonomous Robotic Systems 2, Springer-Verlag, Tokyo, pp. 171-182, 1996.
  6. [6] K. Kawabata, H. Asama, and M. Tanaka, “A study of communication emergence among mobile robots: Simulation of intention transmission,” H. Asama, T. Fukuda, T. Arai, and T. Hasegawa (Eds.), Distributed Autonomous Robotic Systems 5, Springer, pp. 71-80, 2002.
  7. [7] D. Kurabayashi, J. Ota, T. Arai, and E. Yoshida, “Cooperative sweeping by multiple mobile robots,” Proc. IEEE Int. Conf. Robotics Automat., pp. 1744-1749, 1996.
  8. [8] L. E. Parker, “Distributed algorithm for multi-robot observation of multiple moving targets,” Autonomous Robots, Vol.12, No.3, pp. 231-255, 2002.
  9. [9] B. Yamaguchi, “Decentralized coordination for multi-robot exploration,” Robotics Autonomous Syst., Vol.29, No.2-3, pp. 111-118, 1999.
  10. [10] C. Trevai, Y. Fukazawa, H. Yuasa, J. Ota, T. Arai, and H. Asama, “Exploration path generation for multiple mobile robots using a reaction-diffusion equation on a graph,” Integr. Comput-aided Eng., Vol.11, No.3, pp. 195-212, 2004.
  11. [11] L. E. Parker, “ALLIANCE: An architecture for fault-tolerant multi-robot cooperation,” IEEE Trans. Robotics Automat., Vol.18, No.5, pp. 758-768, 1998.
  12. [12] N. Miyata, J. Ota, T. Arai, and H. Asama, “Cooperative transport by multiple mobile robots in unknown static environments associated with real-time task-assignment,” IEEE Trans. Robotics Automat., Vol.18, No.5, pp. 769-780, 2002.
  13. [13] A. Martinoll, K. Easton, and W. Agassounon, “Modeling swarm robotic systems: A case study in collaborative distributed manipulation,” Int. J. Robotics Res., Vol.23, No.4-5, pp. 415-436, 2004.
  14. [14] E. Pagello, A. D'Angelo, C. Ferrari, R. Polesel, R. Rosati, and A. Speranzon, “Emergent behaviors of a robot team performing cooperative tasks,” Adv. Robotics, Vol.17, No.1, pp. 3-19, 2003.
  15. [15] A. Drogoul and J. Ferber, “From Tom thumb to the Dockers: Some experiments with foraging robots,” From Animals and Animats 2, pp. 451-459, 1992.
  16. [16] O. Khatib, “Real-Time obstacle avoidance for manipulators and mobile robots,” Int. Journal of Robotics Research, Vol.5, No.1, pp. 90-98, 1986.
  17. [17] T. Lozano-Perez and M. A. Wesley, “An algorithm for planning Collision-Free Paths Among Polyhedral Obstacles,” Communications of the ACM, Vol.22, No.10, pp. 560-570, 1979.
  18. [18] B. J. Oommen, S. S. Iyengar, N. S. V. Rao, and R. L. Kashyap, “Robot navigation in unknown terrains using learned visibility graphs, Part I: The disjoint convex obstacle case,” IEEE J. Robotics and Automat., Vol.RA-3, No.6, pp. 672-681, 1987.
  19. [19] J. Ota, T. Arai, and Y. Yokogawa, “Distributed strategy-making method in multiple mobile robot system,” Proc. Int. Symp. on Distributed Autonomous Robotic Systems(DARS'94), pp. 123-133, 1994.
  20. [20] A. A. Petrov and I. M. Sirota, “Path Planning by Intelligent Autonomous Robotic Vehicles with Growing World Models,” 2nd IFAC Conf. On Intelligent Autonomous Vehicles 95, pp. 56-59, 1995.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jul. 19, 2024