An adaptive particle filter for mobile robot fault diagnosis

作者：Duan Zhuo hua^*; Fu Ming; Cai Zi xing; Yu Jin xia

来源：Journal of Central South University of Technology, 2006, 13(6): 689-693.

DOI：10.1007/s11771-006-0014-8

• mobile robot
• fault diagnosis
• particle filter
• adaptive

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.

• 出版日期2006-12
• 单位中南大学; 韶关学院; 河南理工大学