Journal of Central South University of Technology

, Volume 13, Issue 6, pp 689–693 | Cite as

An adaptive particle filter for mobile robot fault diagnosis

  • Duan Zhuo-hua  (段琢华)Email author
  • Fu Ming  (傅明)
  • Cai Zi-xing  (蔡自兴)
  • Yu Jin-xia  (于金霞)


An adaptive particle filter for fault diagnosis of dead-reckoning system was presented, which applied a general framework to integrate rule-based domain knowledge into particle filter. Domain knowledge was exploited to constrain the state space to certain subset. The state space was adjusted by setting the transition matrix. Firstly, the monitored mobile robot and its kinematics models, measurement models and fault models were given. Then, 5 kinds of planar movement states of the robot were estimated with driving speeds of left and right side. After that, the possible (or detectable) fault modes were obtained to modify the transitional probability. There are two typical advantages of this method, i.e. particles will never be drawn from hopeless area of the state space, and the particle number is reduced.

Key words

mobile robot fault diagnosis particle filter adaptive 

CLC number



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Copyright information

© Published by: Central South University Press, Sole distributor outside Mainland China: Springer 2006

Authors and Affiliations

  • Duan Zhuo-hua  (段琢华)
    • 1
    • 2
    Email author
  • Fu Ming  (傅明)
    • 1
  • Cai Zi-xing  (蔡自兴)
    • 1
  • Yu Jin-xia  (于金霞)
    • 1
    • 3
  1. 1.Computer Science and Technology Postdoctoral Research Station, School of Information Science and EngineeringCentral South UniversityChangshaChina
  2. 2.Department of Computer ScienceShaoguan UniversityShaoguanChina
  3. 3.Department of Computer Science and TechnologyHenan Polytechnic UniversityJiaozuoChina

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