A Comparative Study between Optimization and Market-Based Approaches to Multi-Robot Task Allocation

This paper presents a comparative study between optimization-based and market-based approaches used for solving the Multirobot task allocation (MRTA) problem that arises in the context of multirobot systems (MRS). The two proposed approaches are used to find the optimal allocation of a number of heterogeneous robots to a number of heterogeneous tasks. The two approaches were extensively tested over a number of test scenarios in order to test their capability of handling complex heavily constrained MRS applications that include extended number of tasks and robots. Finally, a comparative study is implemented between the two approaches and the results show that the optimization-based approach outperforms themarket-based approach in terms of optimal allocation and computational time.

[1]  Maja J. Mataric,et al.  Sold!: auction methods for multirobot coordination , 2002, IEEE Trans. Robotics Autom..

[2]  Leszek Koszalka,et al.  Task Allocation in Mesh Connected Processors with Local Search Meta-heuristic Algorithms , 2010, ACIIDS.

[3]  Reiner Horst,et al.  Introduction to Global Optimization (Nonconvex Optimization and Its Applications) , 2002 .

[4]  Swaroop Darbha,et al.  Heterogeneous, Multiple Depot, Multiple UAV Routing Problem , 2010 .

[5]  Jeffrey S. Rosenschein,et al.  A Domain Theory for Task Oriented Negotiation , 1993, IJCAI.

[6]  Alejandro R. Mosteo Multi-robot task allocation for service robotics: from unlimited to limited communication range , 2010 .

[7]  Ding Ying MULTI-ROBOT COOPERATION METHOD BASED ON THE ANT ALGORITHM , 2003 .

[8]  Anthony Stentz,et al.  An auction-based approach to complex task allocation for multirobot teams , 2006 .

[9]  H. L. Akin,et al.  Q-Learning based Market-Driven Multi-Agent Collaboration in Robot Soccer , 2004 .

[10]  Reid G. Smith,et al.  The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver , 1980, IEEE Transactions on Computers.

[11]  Anthony Stentz,et al.  Time-extended multi-robot coordination for domains with intra-path constraints , 2011, Auton. Robots.

[12]  Nidhi Kalra,et al.  Market-Based Multirobot Coordination: A Survey and Analysis , 2006, Proceedings of the IEEE.

[13]  Fakhri Karray,et al.  Market-Based Framework for Mobile Surveillance Systems , 2012, AIS.

[14]  Michael P. Wellman Market-aware agents for a multiagent world , 1997, Robotics Auton. Syst..

[15]  Marjorie Darrah,et al.  Multiple UAV Dynamic Task Allocation using Mixed Integer Linear Programming in a SEAD Mission , 2005 .

[16]  Lonnie R. Welch,et al.  Heuristic resource allocation algorithms for maximizing allowable workload in dynamic, distributed real-time systems , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

[17]  Çetin Meriçli,et al.  Market-Driven Multi-Agent Collaboration in Robot Soccer Domain , 2005 .

[18]  P. J. Shea,et al.  Group tracking using genetic algorithms , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.

[19]  Subhash Suri,et al.  Improved Algorithms for Optimal Winner Determination in Combinatorial Auctions and Generalizations , 2000, AAAI/IAAI.

[20]  Anthony Stentz,et al.  Traderbots: a new paradigm for robust and efficient multirobot coordination in dynamic environments , 2004 .

[21]  Victor R. Lesser,et al.  Issues in Automated Negotiation and Electronic Commerce: Extending the Contract Net Framework , 1997, ICMAS.

[22]  Xiaomin Li,et al.  Multi-robot Task Allocation Based on Ant Colony Algorithm , 2012, J. Comput..

[23]  Maja J. Matarić,et al.  On multi-robot task allocation , 2003 .

[24]  S. Sariel-Talay,et al.  Multiple Traveling Robot Problem: A Solution Based on Dynamic Task Selection and Robust Execution , 2009, IEEE/ASME Transactions on Mechatronics.

[25]  A. K. Kulatunga,et al.  Simultaneous Planning and Scheduling for Multi-Autonomous Vehicles , 2007, Evolutionary Scheduling.

[26]  M. Golfarelli,et al.  A Task-Swap Negotiation Protocol Based on the Contract Net Paradigm , 2000 .

[27]  Fakhri Karray,et al.  Complex Task Allocation in Mobile Surveillance Systems , 2011, J. Intell. Robotic Syst..

[28]  Luis Montano,et al.  Simulated annealing for multi-robot hierarchical task allocation with MinMax objective , 2006 .

[29]  Swaroop Darbha,et al.  Today's Traveling Salesman Problem , 2010, IEEE Robotics & Automation Magazine.

[30]  Pattie Maes,et al.  Challenger: a multi-agent system for distributed resource allocation , 1997, AGENTS '97.

[31]  T. Bektaş The multiple traveling salesman problem: an overview of formulations and solution procedures , 2006 .

[32]  Deshi Li,et al.  A Multi-Robots Task Allocation Algorithm Based on Relevance and Ability With Group Collaboration , 2010 .

[33]  Yan He,et al.  Multi-robot cooperation method based on the ant algorithm , 2003, SIS.

[34]  Nuzhet Atay,et al.  Mixed-Integer Linear Programming Solution to Multi-Robot Task Allocation Problem , 2006 .

[35]  Tuomas Sandholm,et al.  An Implementation of the Contract Net Protocol Based on Marginal Cost Calculations , 1993, AAAI.

[36]  Alejandro R. Mosteo,et al.  Simulated annealing for multi-robot hierarchical task allocation with flexible constraints and objective functions , 2006 .

[37]  Li Bo,et al.  Multi-task allocation of UCAVs considering time cost and hard time window constraints , 2012, Proceedings of the 31st Chinese Control Conference.

[38]  A. Stentz,et al.  Market-based Approaches for Coordination of Multi-robot Teams at Different Granularities of Interaction , 2004 .

[39]  Wun-Hwa Chen,et al.  A hybrid heuristic to solve a task allocation problem , 2000, Comput. Oper. Res..

[40]  Maja J. Matarić,et al.  A market-based formulation of sensor-actuator network coordination , 2002, AAAI 2002.