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A Generalized Real-Time Obstacle Avoidance Method Without the Cspace Calculation

Journal of Computer Science and Technology volume 20, pages 774–787 (2005)Cite this article

Abstract

An important concept proposed in the early stage of robot path planning field is the shrinking of a robot to a point and meanwhile the expanding of obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision-free path for a point robot among the Cspace obstacles. However, the research experiences have shown that the Cspace transformation is very hard when the following situations occur: 1) both the robot and obstacles are not polygons, and 2) the robot is allowed to rotate. This situation gets even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. For this reason, direct path planning approaches without the Cspace transformation is quite useful and expected. Motivated by the practical requirements of robot path planning, a generalized constrained optimization problem (GCOP) with not only logic AND but also logic OR relationships was proposed and a mathematical solution developed previously. This paper inherits the fundamental ideas of inequality and optimization techniques from the previous work, converts the obstacle avoidance problem into a semi-infinite constrained optimization problem with the help of the mathematical transformation, and proposes a direct path planning approach without Cspace calculation, which is quite different from traditional methods. To show its merits, simulation results in 3D space have been presented.

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Authors and Affiliations

  1. Laboratory for Internet Software Technologies, Institute of Software, Chinese Academy of Sciences, Beijing, 100080, P.R. China

    Yong-Ji Wang, Qiu-Ming Tao & Han Liu

  2. Centre for Systems and Control, University of Glasgow, Glasgow, G12 8QQ, U.K.

    Matthew Cartmell

Authors
  1. Yong-Ji Wang
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  2. Matthew Cartmell
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  3. Qiu-Ming Tao
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  4. Han Liu
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Corresponding author

Correspondence to Yong-Ji Wang.

Additional information

Supported by the joint research project of Chinese Academy of Sciences, P.R. China and Royal Society of United Kingdom under Grant No.20030389, 2003–2006, the National High-Tech Development 863 Program of China under Grant No.2003AA1Z2220, the National Natural Science Foundation of China under Grant No.60373053, and Chinese Academy of Sciences and Chinese State Development Planning Commission for The Hundred Talents Plan of the Chinese Academy of Sciences, 2002–2005.

Yong-Ji Wang is a research professor with the Institute of Software, Chinese Academy of Sciences. Prof. Wang received the B.S. and M.S. degrees from Beijing University of Aeronautics and Astronautics, China, in 1984 and 1987, respectively, and the Ph.D. degree from Edinburgh University, U.K., in 1995. From 1987 to 1991, he was a lecturer with Tianjing University, China. From 1995 to 1998, he was a postdoctoral researcher with Heriot-Watt University, U.K. From 1998 to 2002, he was a researcher fellow with the Department of Mechanical Engineering, Centre of Systems and Control, Glasgow University, U.K. He is currently a supervisor of Ph.D. candidates with Laboratory for Internet Software Technologies, Institute of Software, Chinese Academy of Sciences. Prof. Wang has long been engaged in the research on computer-controlled real-time system, advanced numerical methods, autonomous real-time robot systems, non-linear optimization theory, and real-time hybrid control theory. He has published more than fifty papers in important journals and conferences, including IEEE Transactions, IEE Proceedings, ROBOTICA, ASCE, SIAM, and International Journal of Control, and served as a referee for more than ten important international journals and conferences. He has participated in three significant projects sponsored by the European Community. He was awarded Hong Kong Wang Kuancheng Fund Award, the British Overseas Scholars Fund Award, and Ford Fund Award. He is now mainly involved in the research on real-time system and Internet technology.

Matthew Cartmell has worked since the mid nineteen eighties as a lecturer in dynamics at the Universities of Aberdeen, and Wales (Swansea), then as a senior lecturer in computational mechanics at the University of Edinburgh, and finally since 1998 as professor of applied dynamics at the University of Glasgow. He has held a number of EPSRC, Royal Society, EC, and British Council grants in areas and topics relating to design, vibrations, control, computational modelling, and the mechanics of smart materials. Matthew Cartmell's principal current research interests comprise symbolic computational technologies for analytical solutions to problems in nonlinear vibrations, the dynamics and design of space tether propulsion systems, the dynamics and control of gantry cranes, and the application of shape memory alloys within composite structures for vibration control in machinery.

Qiu-Ming Tao received the B.S. degree from Department of Computer Science and Technology, Nanjing University, China, in 2002. He is currently a Ph.D. candidate of Institute of Software, Chinese Academy of Sciences. His main research interests are software testing, software engineering, and real-time system.

Han Liu received the B.S. degree from Department of Computer, Harbin Institute of Technology, China, in 2002. His main research interests are real-time system and software engineering.

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Wang, YJ., Cartmell, M., Tao, QM. et al. A Generalized Real-Time Obstacle Avoidance Method Without the Cspace Calculation. J Comput Sci Technol 20, 774–787 (2005). https://doi.org/10.1007/s11390-005-0774-x

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  • DOI: https://doi.org/10.1007/s11390-005-0774-x

Keywords

  • path planning
  • obstacle avoidance
  • autonomous underwater vehicle
  • non-linear programming
  • robotics
  • semi-infinite constrained optimization