Multi-robot Task Allocation Using Clustering Method

This paper introduces an approach to solve the task assignment problem for a large number of tasks and robots in an efficient time. This method reduces the size of the state space explored by partitioning the tasks to the number of robotic agents. The proposed method is divided into three stages: first the tasks are partitioned to the number of robots, then robots are being assigned to the clusters optimally, and finally a task assignment algorithm is executed individually at each cluster. Two methods are adopted to solve the task assignment at each cluster, a genetic algorithm and an imitation learning algorithm. To verify the performance of the proposed approach, several numerical simulations are performed. Our empirical evaluation shows that clustering leads to great savings in runtime (up to a factor of 50), while maintaining the quality of the solution.

[1]  A. Volgenant,et al.  A shortest augmenting path algorithm for dense and sparse linear assignment problems , 1987, Computing.

[2]  Tal Shima,et al.  Multiple task assignments for cooperating uninhabited aerial vehicles using genetic algorithms , 2006, Comput. Oper. Res..

[3]  Hyochoong Bang,et al.  Cooperative Task Assignment/Path Planning of Multiple Unmanned Aerial Vehicles Using Genetic Algorithms , 2009 .

[4]  Lior Pachter,et al.  Constrained Optimization for UAV Task Assignment , 2004 .

[5]  Feng Wu,et al.  Online planning for multi-agent systems with bounded communication , 2011, Artif. Intell..

[6]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[7]  David Silver,et al.  Learning to search: Functional gradient techniques for imitation learning , 2009, Auton. Robots.

[8]  Felix Duvallet,et al.  Imitation learning for task allocation , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Steven R. Rasmussen,et al.  Multiple Task Assignment for a UAV Team , 2002 .

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

[11]  L.A.B. Torres,et al.  Development of a Hand-Launched Small UAV for Ground Reconnaissance , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[12]  H. Kuhn.  The Hungarian method for the assignment problem , 1955 .

[13]  Genshe Chen,et al.  Particle Swarm Optimization for Resource Allocation in UAV Cooperative Control , 2004 .

[14]  Mauro Dell'Amico,et al.  Assignment Problems , 1998, IFIP Congress: Fundamentals - Foundations of Computer Science.

[15]  Lior Rokach,et al.  A survey of Clustering Algorithms , 2010, Data Mining and Knowledge Discovery Handbook.

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

[17]  Guilherme A. S. Pereira,et al.  On the development of a small hand-held multi-UAV platform for surveillance and monitoring , 2013, 2013 International Conference on Unmanned Aircraft Systems (ICUAS).

[18]  Brett Browning,et al.  A survey of robot learning from demonstration , 2009, Robotics Auton. Syst..

[19]  Jonathan P. How,et al.  COORDINATION AND CONTROL OF MULTIPLE UAVs , 2002 .

[20]  Jean-Yves Potvin,et al.  Genetic Algorithms for the Traveling Salesman Problem , 2005 .

[21]  Eugene L. Lawler,et al.  Traveling Salesman Problem , 2016 .

[22]  Stefan Schaal,et al.  Robot Programming by Demonstration , 2009, Springer Handbook of Robotics.