Identification of abnormal movement state and avoidance strategy for mobile robots
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Abnormal movement states for a mobile robot were identified by four multi-layer perceptron. In the presence of abnormality, avoidance strategies were designed to guarantee the safety of the robot. Firstly, the kinematics of the normal and abnormal movement states were exploited, 8 kinds of features were extracted. Secondly, 4 multi-layer perceptrons were employed to classify the features for four 4-driving wheels into 4 kinds of states, i.e. normal, blocked, deadly blocked, and slipping. Finally, avoidance strategies were designed based on this. Experiment results show that the methods can identify most abnormal movement states and avoid the abnormality correctly and timely.
Key wordsmobile robot abnormal movement state avoidance strategy
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- Roumeliotis S I, Sukhatme G S, Bekey G A. Sensor fault detection and identification in a mobile robot[C]// IEEE/RSJ International Conference on Intelligent Robots and Systems. Victoria: IEEE Press, 1998: 1383–1388.Google Scholar
- Goel P, Dedeoglu G, Roumeliotis S I, et al. Fault detection and identification in a mobile robot using multiple model estimation and neural network[C]// IEEE International Conference on Robotics & Aufomation. San Francisco: IEEE Press, 2000: 2302–2309.Google Scholar
- Washington R. On-board real-time state and fault identification for rovers[C]// IEEE Int’l Conference on Robotics & Automation. San Francisco: IEEE Press, 2000: 1175–1181Google Scholar
- Verma V, Gordon G, Simmons R. Efficient monitoring for planetary rovers[C]// International Symposium on Artificial Intelligence and Robotics in Space. Nara: IEEE Press, May, 2003.Google Scholar
- Dixon W E, Walker I D, Dawson D M. Fault detection for wheeled mobile robots with parametric uncertainty[C]// IEEE/ASME Intl’ Conference on Advanced Intelligent Mechatronics. Como: IEEE Press, 2001: 1245–1250.Google Scholar
- DUAN Zhuo-hua, CAI Zi-xing, YU Jin-xia. Fault diagnosis and fault tolerant control for wheeled mobile robots under unknown environments: A survey[J]. Robot, 2005, 27(4): 373–379.(in Chinese)Google Scholar
- TING H N, YUNUS J. Speaker-independent Malay vowel recognition of children using multi-layer perceptron[C]// 2004 IEEE Region 10 Conference Proceedings: Analog and Digital Techniques in Electrical Engineering. Chiangmai: IEEE Press, 2004: A68–A71.Google Scholar
- YU Dong-jun, ZHAO Hai-tao, YANG Jing-yu. Face recognition: An approach based on feature fusion and neural network[J]. Journal of System Simulation, 2005, 17(5): 1179–1181, 1184.Google Scholar
- CAI Zi-xing, ZOU Xiao-bing, WANG Lu, et al. A research on mobile robot navigation control in unknown environment: objectives, design and experiences[C]// Proceedings of Korea-Sino Symposium on Intelligent Systems. Busan: 2004: 57–63.Google Scholar