The Combination of Attractive Regions and Pre-images in Motion Planning
Affiliation:
1. Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong; 2. Department of Computation, UMIST, UK
Abstract
The general purpose of sensors is to obtain information on the system. However, in many cases, sensors cannot provide all the information on the system being controlled. On the other hand, the controller system does not need all the information in the process to guide the system into the goal, which provides the opportunity of utilizing simple sensors and then reducing the operational cost and time. The key point is that the information needed from the strategy should match the information which can be provided from the sensory signal. The difficulty left is due to the dependence between the sensor selection and strategy investigation. In other words, the two issues, (a) how to select the sensors and (b) how to form the commanded action, depend on each other. Benefited from the pre-image concept proposed by Lozano-Perez, Mason and Taylor1 and the attractive region concept proposed in the author’s previous work (2000), a logical method to design the pre-image of the goal is presented in this paper. Then the requirement of sensory feedback and the design of commanded action are given. Within this principle, the strategies in the robotic assembly with force sensors are investigated and applied in experiments in the present paper. It should be noted that the robotic assembly plays an important role in manufacturing automation. Also the assembly strategy presented here can be used with any machine.
Publisher
ASME International
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering
Reference30 articles.
1. Lozano-Perez, T., Mason, M. T., and Taylor, R. H., 1983, “Automatic Synthesis of Fine Motion Strategies,” 1st International Symp. of Robotics Research, pp. 65–96. 2. Lazanas, A., and Latombe, J. C., 1995, “Motion Planning with Uncertainty: A Landmark Approach, Motion Planning with Uncertainty: A Landmark Approach,” Artif. Intel., 76, pp. 287–317. 3. Erdmann, M., 1984, “On Motion Plannign with Uncertainty,” Tech Report 810, AI Lab., MIT, Cambridge, MA. 4. Erdmann, M.
, 1986, “Using Backprojections for Fine Motion Planning with Uncertainty,” Int. J. Robot. Res., 5, No. 1, pp. 19–45. 5. Canny, J. F., and Goldberg, K. Y., 1994, “RISC for Industrial Robotics: Recent Results and Open Problems,” IEEE International Conference on Robotics and Automation.
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