Connectivity vs. control: Using directional and positional cues to stabilize routing in robot networks

Various coordination algorithms have been proposed for robot networks. One of the fundamental assumptions of such algorithms is that the underlying connectivity graph be stable. Adhoc routing protocols attempt to optimize the path from source to destination and do not guarantee route stability. We bridge this gap by providing directional and locational cues to the routing protocol to provide more stable routes. We implement our ideas on optimized link state routing (OLSR), a popular proactive routing protocol for robot networks. Our results show that simple directional and locational cues can achieve up to 20% fewer route switches in comparison to the basic version of OLSR.

[1]  Pradeep K. Khosla,et al.  Distributed surveillance and reconnaissance using multiple autonomous ATVs: CyberScout , 2002, IEEE Trans. Robotics Autom..

[2]  Gaurav S. Sukhatme,et al.  Using Local Geometry for Tunable Topology Control in Sensor Networks , 2009, IEEE Transactions on Mobile Computing.

[3]  Ali Jadbabaie,et al.  Decentralized Control of Connectivity for Multi-Agent Systems , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[4]  Deborah Estrin,et al.  Advances in network simulation , 2000, Computer.

[5]  Nathan Michael,et al.  Bearing-Only Control Laws For Balanced Circular , 2008 .

[6]  Paolo Santi.  Topology control in wireless ad hoc and sensor networks , 2005 .

[7]  Paramvir Bahl,et al.  A cone-based distributed topology-control algorithm for wireless multi-hop networks , 2005, IEEE/ACM Transactions on Networking.

[8]  Andrew Howard,et al.  Multi-robot Simultaneous Localization and Mapping using Particle Filters , 2005, Int. J. Robotics Res..

[9]  Gaurav S. Sukhatme,et al.  Tracking Targets Using Multiple Robots: The Effect of Environment Occlusion , 2002, Auton. Robots.

[10]  Gaurav S. Sukhatme,et al.  Experiments with a Large Heterogeneous Mobile Robot Team: Exploration, Mapping, Deployment and Detection , 2006, Int. J. Robotics Res..

[11]  Gerhard Lakemeyer,et al.  RoboCup 2006: Robot Soccer World Cup X , 2006, RoboCup.

[12]  George J. Pappas,et al.  Distributed formation control with permutation symmetries , 2007, 2007 46th IEEE Conference on Decision and Control.

[13]  Francesco Bullo,et al.  Distributed Control of Robotic Networks , 2009 .

[14]  J. Baillieul,et al.  Problems in Decentralized Sensor-Actuator Networks , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[15]  Mehran Mesbahi,et al.  On maximizing the second smallest eigenvalue of a state-dependent graph Laplacian , 2006, IEEE Transactions on Automatic Control.

[16]  Philippe Jacquet,et al.  Optimized Link State Routing Protocol (OLSR) , 2003, RFC.

[17]  Nitin H. Vaidya,et al.  Location-aided routing (LAR) in mobile ad hoc networks , 1998, MobiCom '98.