Distributed Fault Detection and Isolation for Flocking in a Multi-robot System with Imperfect Communication

In this paper, we focus on distributed fault detection and isolation (FDI) for a multi-robot system where multiple robots execute a flocking task. Firstly, we propose a fault detection method based on the local-information-exchange and sensor-measurement technologies to cover cases of both perfect communication and imperfect communication. The two detection technologies can be adaptively selected according to the packet loss rate (PLR). Secondly, we design a fault isolation method, considering a situation in which faulty robots still influence the behaviours of other robots. Finally, a complete FDI scheme, based on the proposed detection and isolation methods, is simulated in various scenarios. The results demonstrate that our FDI scheme is effective.

[1]  Guang-Hong Yang,et al.  Fault detection for networked control systems subject to quantisation and packet dropout , 2013, Int. J. Syst. Sci..

[2]  Marios M. Polycarpou,et al.  Decentralized fault detection in a class of large-scale nonlinear uncertain systems , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[3]  Marios M. Polycarpou,et al.  Distributed Fault Diagnosis With Overlapping Decompositions: An Adaptive Approximation Approach , 2009, IEEE Transactions on Automatic Control.

[4]  Naixue Xiong,et al.  A Decentralized and Adaptive Flocking Algorithm for Autonomous Mobile Robots , 2008, 2008 The 3rd International Conference on Grid and Pervasive Computing - Workshops.

[5]  Leonid Perlovsky,et al.  Maximum Likelihood Joint Tracking and Association in Strong Clutter , 2013 .

[6]  Gyemin Lee,et al.  EM algorithms for multivariate Gaussian mixture models with truncated and censored data , 2012, Comput. Stat. Data Anal..

[7]  Mohammad Aldeen,et al.  Observer-based fault detection and identification scheme for power systems , 2006 .

[8]  Steven X. Ding,et al.  Advanced design scheme for fault tolerant distributed networked control systems , 2008 .

[9]  Riccardo M. G. Ferrari,et al.  Distributed fault diagnosis with overlapping decompositions and consensus filters , 2007, 2007 American Control Conference.

[10]  Karl Henrik Johansson,et al.  Distributed fault detection for interconnected second-order systems , 2011, Autom..

[11]  Li Da-zhou.  Design and Implementation of Prolonging Life Cycle of WSN in Data Collection , 2012 .

[12]  J. Toner,et al.  Flocks, herds, and schools: A quantitative theory of flocking , 1998, cond-mat/9804180.

[13]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[14]  Marios M. Polycarpou,et al.  Distributed Fault Detection and Isolation of Large-Scale Discrete-Time Nonlinear Systems: An Adaptive Approximation Approach , 2012, IEEE Transactions on Automatic Control.

[15]  Antonio Bicchi,et al.  Dynamic distributed intrusion detection for secure multi-robot systems , 2009, 2009 IEEE International Conference on Robotics and Automation.

[16]  Khashayar Khorasani,et al.  Fault Detection and Isolation of discrete-time Markovian jump linear systems with application to a network of multi-agent systems having imperfect communication channels , 2009, Autom..

[17]  Wenwu Yu,et al.  An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination , 2012, IEEE Transactions on Industrial Informatics.

[18]  Nak Young Chong,et al.  Adaptive Flocking of Robot Swarms: Algorithms and Properties , 2008, IEICE Trans. Commun..

[19]  Riccardo M. G. Ferrari,et al.  Distributed fault detection and isolation of large-scale nonlinear systems: an adaptive approximation approach , 2009 .

[20]  Jianxun He,et al.  Mixture model based multivariate statistical analysis of multiply censored environmental data , 2013 .

[21]  Nak Young Chong,et al.  Low-Cost Dual Rotating Infrared Sensor for Mobile Robot Swarm Applications , 2011, IEEE Transactions on Industrial Informatics.

[22]  Ernst Scholtz,et al.  Graphical observer design suitable for large-scale DAE power systems , 2008, 2008 47th IEEE Conference on Decision and Control.