Fault tolerant localization for teams of distributed robots

To combine sensor information from distributed robot teams, it is critical to know the locations of all the robots relative to each other. This paper presents a novel fault tolerant localization algorithm developed for centimeter-scale robots, called Millibots. To determine their locations, the Millibots measure the distances between themselves with an ultrasonic distance sensor. They then combine these distance measurements with dead reckoning in a maximum likelihood estimator. The focus of this paper is on detecting and isolating measurement faults that commonly occur in this localization system. Such failures include dead reckoning errors when the robots collide with undetected obstacles, and distance measurement errors due to destructive interference between direct and multi-path ultrasound wavefronts. Simulations show that the fault tolerance algorithm accurately detects erroneous measurements and significantly improves the reliability and accuracy of the localization system.

[1]  R. Fletcher.  Practical Methods of Optimization , 1988 .

[2]  Gaurav S. Sukhatme,et al.  Sensor fault detection and identification in a mobile robot , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[3]  Deborah Estrin,et al.  Robust range estimation using acoustic and multimodal sensing , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[4]  Gaurav S. Sukhatme,et al.  Fault detection and identification in a mobile robot using multiple-model estimation , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[5]  Joseph R. Cavallaro,et al.  Robotic fault detection and fault tolerance: A survey , 1994 .

[6]  Balbir S. Dhillon,et al.  Robotic systems probabilistic analysis , 1997 .

[7]  Lindsay Kleeman,et al.  Optimal estimation of position and heading for mobile robots using ultrasonic beacons and dead-reckoning , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[8]  A. Gosavi,et al.  General Statistics , 2000, 2018 Inland Transport Statistics for Europe and North America.

[9]  Balbir S. Dhillon.  Robot reliability and safety , 1991 .

[10]  D. E. Manolakis,et al.  Efficient solution and performance analysis of 3-D position estimation by trilateration , 1996 .

[11]  Christiaan J. J. Paredis,et al.  Heterogeneous Teams of Modular Robots for Mapping and Exploration , 2000, Auton. Robots.

[12]  Alessandro Birolini.  Reliability Engineering: Theory and Practice , 1999 .

[13]  Liqiang Feng,et al.  Navigating Mobile Robots: Systems and Techniques , 1996 .

[14]  Gaurav S. Sukhatme,et al.  Fault detection and identification in a mobile robot using multiple model estimation and neural network , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[15]  Christiaan J. J. Paredis,et al.  A Beacon System for the Localization of Distributed Robotic Teams , 1999 .

[16]  Lynne E. Parker,et al.  ALLIANCE: an architecture for fault tolerant multirobot cooperation , 1998, IEEE Trans. Robotics Autom..

[17]  Hugh F. Durrant-Whyte,et al.  Mobile robot localization by tracking geometric beacons , 1991, IEEE Trans. Robotics Autom..

[18]  Elizabeth R. Stuck,et al.  Map updating and path planning for real-time mobile robot navigation , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).