A combined auction mechanism for online instant planning in multi-robot transportation problem

  • Jonban, Mansour Selseleh (Young Researchers and Elite Club, Ahar Branch, Islamic Azad University) ;
  • Akbarimajd, Adel (Electrical Engineering Department, Faculty of Engineering, University of Mohaghegh Ardabili) ;
  • Hassanpour, Mohammad (Young Researchers and Elite Club, Ahar Branch, Islamic Azad University)
  • Received : 2017.04.26
  • Accepted : 2018.12.13
  • Published : 2018.09.25


Various studies have been performed to coordinate robots in transporting objects and different artificial intelligence algorithms have been considered in this field. In this paper, we investigate and solve Multi-Robot Transportation problem by using a combined auction algorithm. In this algorithm each robot, as an agent, can perform the auction and allocate tasks. This agent tries to clear the auction by studying different states to increase payoff function. The algorithm presented in this paper has been applied to a multi-robot system where robots are responsible for transporting objects. Using this algorithm, robots are able to improve their actions and decisions. To show the excellence of the proposed algorithm, its performance is compared with three heuristic algorithms by statistical simulation approach.


multi-agent system;multi-robot coordination;multi-robot transportation;task allocation;auction mechanism


  1. Smith, R.G. (1980), "The contract net protocol: High-level communication and control in a distributed problem solver", IEEE T. Comput., C29(12), 1104-1113.
  2. Song, T., Yan, X., Liang, A., Chen, K. and Guan, H. (2009), "A distributed bidirectional auction algorithm for multirobot coordination", Proceedings of the International Conference on Research Challenges in Computer Science, Shanghai, China.
  3. Sycara, K. (1998), "Multiagent systems", AI Mag., 19(2), 79-92.
  4. Wawerla, J. and Vaughan, R.T. (2010), "A fast and frugal method for team-task allocation in a multi-robot transportation system", Proceedings of the International Conference on Robotics and Automation (ICRA), Anchorage, Alaska, U.S.A., May.
  5. Wu, J., Xu, X., Wang, J. and He, H.G. (2011), "Recent advances of reinforcement learning in multi-robot systems: A survey", Control Decision, 26(11), 1601-1610.
  6. Zhang, K., Collins Jr, E.G. and Barbu, A. (2013), "Efficient Stochastic Clustering Auctions for Agent-Based Collaborative Systems", J. Intell. Robot. Syst., 72(3-4), 541-558.
  7. Zheng, X. and Koenig, S. (2009), "Negotiation with reaction functions for solving complex task allocation problems", Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, Missouri, U.S.A., October.
  8. Zlot, R. and Stentz, A. (2005), "Market-based multirobot coordination for complex tasks", Int. J. Robot. Res., 25(1), 73-101.
  9. Aarts, E.H. and Lenstra, J.K. (1997), Local Search in Combinatorial Optimization, John Wiley and Sons, London, U.K.
  10. Akbarimajd, A., Lotfi, A., Jonban, M.S. and Hassanpour, M. (2014), "A combinatorial auction algorithm for a multi-robot transportation problem", Proceedings of the 3rd International Conference on Machine Learning and Computer Science (IMLCS'2014), Dubai, UAE, January.
  11. Barbu, A. and Zhu, S. (2005), "Generalizing swendsen-wang to sampling arbitrary posterior probabilities", IEEE T. Pattern Anal. Machine Intell., 27(8), 1239-1253.
  12. Cerquides, J., Farinelli, A., Meseguer, P. and Ramchurn, S. D. (2014), "A tutorial on optimization for multiagent systems", Comput. J., 57(6), 799-824.
  13. Cramton, P., Shoham, Y. and Steinberg, R. (2006), Combinatorial Auctions, MIT Press, Cambridge, Massachusetts, U.S.A.
  14. Dasgupta, P. (2011), Multi-Robot Task Allocation for Performing Cooperative Foraging Tasks in an Initially Unknown Environment, in Innovations in Defence Support Systems-2, Springer, Berlin, Heidelberg, Germany, 5-20.
  15. Dias, M.B. and Stentz, A. (2002), "Opportunistic optimization for market-based multirobot control", Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '02), Lausanne, Switzerland, September-October.
  16. Dias, M.B. and Stentz, A. (2004), "Traderbots: A new paradigm for robust and efficient multirobot coordination in dynamic environments", Robotics Institute, Carnegie Mellon University, Pittsburg, Pennsylvania, U.S.A.
  17. Garcia, P., Caamano, P., Bellas, F. and Duro, R.J. (2009), "A behavior based architecture with auction-based task assignment for multi-robot industrial applications", Proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, Santiago de Compostela, Spain, June.
  18. Geman, S. and Geman, D. (1984), "Stochastic relaxation, gibbs distributions, and the bayesian restoration of images", IEEE T. Pattern Anal. Machine Intell., 6(6), 721-741.
  19. Gerkey, B.P. (2003), "On multi-robot task allocation", Ph.D. Thesis, University of Southern California, Los Angeles, California, U.S.A.
  20. Hoos, H. and Boutilier, C. (2000), "Solving combinatorial auctions using stochastic local search", Proceedings of the 7th National Conference on American Association for Artificial Intelligence (AAAI), Saint Paul, Minnesota, U.S.A.
  21. Jonban, M.S., Akbarimajd, A. and Javidan, J. (2015), "Intelligent fault tolerant energy management system with layered architecture for a photovoltaic power plant", J. Solar Energy Eng., 137(1), 011004.
  22. Kalra, N., Zlot, R.M., Dias, M.B. and Stentz, A. (2006), "Market-based multirobot coordination: A survey and analysis", Proc. IEEE, 94(7), 1257-1270.
  23. Koenig, S., Tovey, C.A., Lagoudakis, M.G., Markakis, V., Kempe, D., Keskinocak, P., Kleywegt, A.J., Meyerson, A. and Jain, S. (2006), "The power of sequential single-item auctions for agent coordination", Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Boston, Massachusetts, U.S.A., July.
  24. Koenig, S., Tovey, C.A., Zheng, X. and Sungur, I. (2007), "Sequential bundle-bid single-sale auction algorithms for decentralized control", Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, January.
  25. Lee, D.H., Na, K.I. and Kim, J.H. (2010), "Task and role selection strategy for multi-robot cooperation in robot soccer. Trends in intelligent robotics", Commun. Comput. Inform. Sci., 103(3),170-177.
  26. Ljesnjanin, M. and Velagic, J. (2009), "A market based approach for complex task allocation for wireless network based multi-robot system", Proceedings of the 22nd International Symposium on Information, Communication and Automation Technologies, Bosnia, Serbia, October.
  27. Mataric, M.J., Sukhatme, G.S. and Ostergaard, E. (2003), "Multi-robot task allocation in uncertain environments", Autonom. Robots, 14(2-3), 255-263.
  28. Nanjanath, M. and Gini, M. (2006), "Auctions for task allocation to robots", Proceedings of the International Conference on Intelligent Autonomous Systems, Tokyo, Japan, March.
  29. Parker, L.E. (2012), "Decision making as optimization in multi-robot teams", Proceedings of the International Conference on Distributed Computing and Internet Technology, Bhubaneswar, India, February.
  30. Sandholm, T. (2002), "Algorithm for optimal winner determination in combinatorial auctions", Artif. Intell., 135(1-2), 1-54.
  31. Simzan, G., Akbarimajd, A. and Khosravani, M. (2011), "A market based distributed cooperation mechanism in a multi-robot transportation problem", Proceedings of the International Conference on Intelligent System Design and Application, Cordoba, Spain, November.