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Real-time path planning procedure for a whole-sensitive robot arm manipulator*

Published online by Cambridge University Press:  09 March 2009

Edward Cheung
Affiliation:
N AS A Goddard Space Flight Center/Jackson & Tull, Code 714–1, Bldg. T-ll-B, Greenbelt, MD 20771 (USA).
Vladimir Lumelsky
Affiliation:
University of Wisconsin (USA).

Summary

We consider the problem of sensor-based motion planning for a three-dimensional robot arm manipulator operating among unknown obstacles. When every point of the robot body is subject to potential collision. The corresponding planning system must include these four basic components: sensor hardware; real-time signal/sensory data processing hardware/software; a local step planning subsystem that works at the basic sample rate of the arm; and finally, a subsystem for global planning. The arm sensor system developed at Yale University presents a proximity sensitive skin that covers the whole body of the arm and consists of an array of discrete active infrared sensors that detect obstacles by processing reflected light. The sensor data then undergoes low level processing via a step planning procedure, which converts sensor information into local normals at the contact points in the configuration space of the robot. This paper presents preliminary results on the fourth component, a real-time algorithm that realizes the upper, global level of planning. Based on the current collection of local normals, the algorithm generates preferable directions of motion around obstacles, so as to guarantee reaching the target position if it is reachable. Experimental results from testing the developed system are also discussed.

Type
Article
Copyright
Copyright © Cambridge University Press 1992

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References

1.Karlen, J.P., Thompson, J.M., Farrell, J.D. and Vold, H.I., “Reflexive Obstacle Avoidance for Kinematically-Redundant ManipulatorsNASA Conference on Space Telerobotics,Pasadena California (01, 1989) pp. 672677.Google Scholar
2.Cheung, E. and Lumelsky, V., “Development of Sensitive Skin for a 3d Robot Arm Operating in an Uncertain EnvironmentProc. 1989 IEEE Conference on Robotics and Automation,Scottsdale, AZ (05, 1989) pp. 10561061.Google Scholar
3.Gordon, S. and Townsend, W., “Integration of Tactile-Force and Joint Torque Information in a Whole-Arm ManipulatorsProc. 1989 IEEE Conference on Robotics and Automation, Scottsdale, AZ (05, 1989) pp. 464469.Google Scholar
4.Hemami, H., “Differential Surface Model for Tactile Perception of Shape and On-Line Tracking of FeaturesIEEE J. Systems, Man, and Cybernetics 312315 (03/04, 1988).Google Scholar
5.Lumelsky, V. and Stepanov, A., “Path Planning Strategies for a Point Mobile Automaton Moving Amidst Unknown Obstacles of Arbitrary ShapeAlgorithmica (Springer–Verlag) 2, 403430 (1987).CrossRefGoogle Scholar
6.Cheung, E. and Lumelsky, V., “Motion Planning for Robot Arm Manipulators with Proximity SensorsProc. 1988 IEEE Conference on Robotics and Automation,Philadelphia, PA (04, 1988) pp. 740745.Google Scholar
7.Sun, K. and Lumelsky, V., “Motion Planning with Uncertainty for a 3d Cartesian Robot Arm” 5th International Symposium on Robotics Research, Tokyo, Japan (08, 1989) pp. 5764.Google Scholar
8.Sedgewick, R., Algorithms (Addison-Wesley Publishing Co. Reading, MA, 1984).Google Scholar