Advertisement

Journal of Central South University of Technology

, Volume 13, Issue 6, pp 683–688 | Cite as

Identification of abnormal movement state and avoidance strategy for mobile robots

  • Cai Zi-xing  (蔡自兴)
  • Duan Zhuo-hua  (段琢华)Email author
  • Zhang Hui-tuan  (章慧团)
  • Yu Jin-xia  (于金霞)
Article

Abstract

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 words

mobile robot abnormal movement state avoidance strategy 

CLC number

TP24 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    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
  2. [2]
    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
  3. [3]
    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
  4. [4]
    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
  5. [5]
    Kawabata K, Okina S, Fujii T, et al. A system for self-diagnosis of an autonomous mobile robot using an internal state sensory system: Fault detection and coping with the internal condition[J]. Advanced Robotics, 2003(9): 925–950.CrossRefGoogle Scholar
  6. [6]
    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
  7. [7]
    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
  8. [8]
    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
  9. [9]
    Purushothama G K, Narendranath A U, Thukaram D, et al. ANN applications in fault locators[J]. International Journal of Electrical Power and Energy System, 2001, 23(6): 491–506.CrossRefGoogle Scholar
  10. [10]
    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
  11. [11]
    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
  12. [12]
    Alexander J C, Maddocks J H. On the kinematics of wheeled mobile robots[J]. International Journal of Robotics Research, 1989, 8(5): 15–27.CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  • Cai Zi-xing  (蔡自兴)
    • 1
  • Duan Zhuo-hua  (段琢华)
    • 1
    • 2
    Email author
  • Zhang Hui-tuan  (章慧团)
    • 1
  • Yu Jin-xia  (于金霞)
    • 1
    • 3
  1. 1.School of Information Science and EngineeringCentral South UniversityChangshaChina
  2. 2.School of Information EngineeringShaoguan UniversityShaoguanChina
  3. 3.Department of Computer Science and TechnologyHenan Polytechnic UniversityJiaozuoChina

Personalised recommendations