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Fuzzy Logic-based Techniques for Motion Planning of a Robot Manipulator Amongst Unknown Moving Obstacles

Published online by Cambridge University Press:  09 March 2009

Anupam Bagchi  and
Himanshu Hatwal
Anupam Bagchi
Affiliation:
Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, 208 016 (India)
Himanshu Hatwal
Affiliation:
Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, 208 016 (India)
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Summary

An algorithm for kinematic motion planning of redundant planar robots, having revolute joints, in an unknown dynamic environment is presented. Distance ranging sensors, mounted on the body of each manipulator link, are simulated here to estimate the proximity of an obstacle. The sensory data is analyzed through a fuzzy controller which estimates whether a collision is imminent, and if so, employs a geometric approach to compute the joint movements necessary to avoid the collision. Obstacles can sometimes move uncompromisingly in the environment attempting a deliberate collision. Strategies to deal with such cases are presented and recovery procedures to circumvent the obstacle from tight corners are suggested. Cases of link overlap have been avoided by considering each link as a body which is sensed as an obstacle by every other link of the same manipulator. Suitable examples are presented to demonstrate the algorithm.

Keywords

Fuzzy LogicRedundant Manipulator, Obstacle AvoidanceMotion Planning
Type
Research Article
Information
Robotica , Volume 10 , Issue 6 , November 1992 , pp. 563 - 574
Copyright
Copyright © Cambridge University Press 1992

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References

1.Lozano-Perez, T., “Spatial Planning: A Configuration Space Approach” IEEE Trans. Comp. C–32, 108–120 (02, 1983).CrossRefGoogle Scholar
2.Khatib, O., “RealC–time obstacle avoidance for manipulators and mobile robots” Int. J. Robotics Research 5(1), 90–98 (1986).CrossRefGoogle Scholar
3.Canny, John F., “The Complexity of Robot Motion Planning” Ph. D Dissertation (Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, 1987).Google Scholar
4.Volpe, R. and Khosla, P., “A strategy for obstacle avoidance and approach using super quadrics potential functions” Robotics Research, The Fifth International Symposium 445–452 (1989).Google Scholar
5.Lumelsky, V.J. and Stepanov, A.A., “Dynamic Path Planning for a mobile Automaton with Limited Information on the Environment” IEEE Transactions on Automatic Control AC–31, No. 11, 1058–1063 (11, 1986).CrossRefGoogle Scholar
6.Lumelsky, V.J., “Dynamic Path Planning for a Planar Articulated Robot Arm Moving Amidst Unknown Obstacles” Automatica J. Int. Fed. Automatic Control (IFAC) 551–570 (09 1987).Google Scholar
7.J, Vladmir.. Lumelsky, “Effect of Kinematics on Dynamic Path Planning for Planar Robot Arms Moving Amidst Unknown Obstacles” IEEE J. Robotics and Automation RA–3, No. 3, 207–223 (06, 1987).Google Scholar
8.Sun, K. and Lumelsky, V., “Computer simulation of sensor-based robot collision avoidance in an unknown environment” Robotica 5, Part 4, 291–302 (12 1987).CrossRefGoogle Scholar
9.Lumelsky, Vladimir and Sun, Kang, “A Unified Methodology for Motion Planning with Uncertainty for 2D and 3D Two–Link Robot Arm Manipulators” Int. J. Robotics Research 9, No. 5, 89–104 (10, 1990).CrossRefGoogle Scholar
10.Sun, Kang and Lumelsky, V., “Motion Planning with Uncertainty for a 3d Cartesian Robot Arm” Robotics Research, The Fifth International Symposium 417–424 (1989).Google Scholar
11.Bagchi, A. and Hatwal, H., “A solution strategy for collision avoidance of multiple bodies moving on a plane using fuzzy logic” Proc. Int. Sym. Intelligent Robotics, Bangalore (01, 1991).Google Scholar
12.Novák, V., Fuzzy Sets and their Applications (Adam Hilger, Bristol, 1989).Google Scholar
13.Zadeh, L.A., “Outline of a New Approach to the Analysis of Complex System and Decision Processes” IEEE Trans, on System Man and Cybernetics, SMC–3, No. 1, 28–44 (1973).Google Scholar