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A new potential field-based algorithm for path planning
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AI
DOI：10.1007/BF00339664.png)
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Abstract
En 中文
In this paper, the path-planning problem is considered. We introduce a new potential function for path planning that has the remarkable feature that it is free from any local minima in the free space irrespective of the number of obstacles in the configuration space. The only global minimum is the goal configuration whose region of attraction extends over the whole free space. We also propose a new method for path optimization using an expanding sphere that can be used with any potential or penalty function. Simulations using a point mobile robot and smooth obstacles are presented to demonstrate the qualities of the new potential function. Finally, practical considerations are also discussed for nonpoint robots.
Keywords:
smooth objects
potential function
local minimum
path optimization
Journal
J
IF:
2.8
Papers:
3.8K
Citations:
6.9K
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