Distributed coverage with mobile robots on a graph: Locational optimization

This paper presents decentralized algorithms for coverage with mobile robots on a graph. Coverage is an important capability of multi-robot systems engaged in a number of different applications, including placement for environmental modeling, deployment for maximal quality surveillance, and even coordinated construction. We use distributed vertex substitution for locational optimization and equal mass partitioning, and the controllers minimize the corresponding cost functions. We prove that the proposed controller with two-hop communication guarantees convergence to the locally optimal configuration. We evaluate the algorithms in simulations and also using four mobile robots.

[1]  Joseph E. Flaherty,et al.  Parallel adaptive mesh refinement and redistribution on distributed memory computers , 1994 .

[2]  Shinichi Hirai,et al.  Robust real time material classification algorithm using soft three axis tactile sensor: Evaluation of the algorithm , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[3]  Ruggero Carli,et al.  Discrete Partitioning and Coverage Control for Gossiping Robots , 2010, IEEE Transactions on Robotics.

[4]  Matthew Faulkner,et al.  Experiments in decentralized robot construction with tool delivery and assembly robots , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  Howie Choset,et al.  Coverage Path Planning: The Boustrophedon Cellular Decomposition , 1998 .

[6]  J. Reese,et al.  Solution methods for the p-median problem: An annotated bibliography , 2006 .

[7]  J. Beasley Lagrangean heuristics for location problems , 1993 .

[8]  Qian Wang,et al.  The equitable location problem on the plane , 2007, Eur. J. Oper. Res..

[9]  Max Donath,et al.  American Control Conference , 1993 .

[10]  Mac Schwager,et al.  Decentralized, Adaptive Control for Coverage with Networked Robots , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[11]  Mac Schwager,et al.  Decentralized, Adaptive Coverage Control for Networked Robots , 2009, Int. J. Robotics Res..

[12]  Shahid H. Bokhari,et al.  A Partitioning Strategy for Nonuniform Problems on Multiprocessors , 1987, IEEE Transactions on Computers.

[13]  Sonia Martínez,et al.  Coverage control for mobile sensing networks , 2002, IEEE Transactions on Robotics and Automation.

[14]  M. Erwig The graph Voronoi diagram with applications , 2000 .

[15]  Y. Kallinderis,et al.  Parallel dynamic load-balancing algorithm for three-dimensional adaptive unstructured grids , 1994 .

[16]  Elon Rimon,et al.  Spanning-tree based coverage of continuous areas by a mobile robot , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[17]  David S. Johnson,et al.  Some simplified NP-complete problems , 1974, STOC '74.

[18]  Howie Choset,et al.  Coverage for robotics – A survey of recent results , 2001, Annals of Mathematics and Artificial Intelligence.

[19]  Polly Bart,et al.  Heuristic Methods for Estimating the Generalized Vertex Median of a Weighted Graph , 1968, Oper. Res..

[20]  I. Babuska,et al.  Acta Numerica 2003: Survey of meshless and generalized finite element methods: A unified approach , 2003 .

[21]  Vladimir J. Lumelsky,et al.  Polygon Area Decomposition for Multiple-Robot Workspace Division , 1998, Int. J. Comput. Geom. Appl..

[22]  John E. Beasley,et al.  OR-Library: Distributing Test Problems by Electronic Mail , 1990 .

[23]  Bruce Hendrickson,et al.  An empirical study of static load balancing algorithms , 1994, Proceedings of IEEE Scalable High Performance Computing Conference.