How to avoid that the robot gets trapped in local minimum?

Posted by nesmoht on Stack Overflow See other posts from Stack Overflow or by nesmoht
Published on 2010-02-04T12:43:14Z Indexed on 2010/05/17 4:10 UTC
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Hi,

I have some time occupying myself with motion planning for robots, and have for some time wanted to explore the possibility of improving the opportunities as "potential field" method offers. My challenge is to avoid that the robot gets trapped in "local minimum" when using the "potential field" method. Instead of using a "random walk" approach to avoid that the robot gets trapped I have thought about whether it is possible to implement a variation of A* which could act as a sort of guide for precisely to avoid that the robot gets trapped in "local minimum".

Is there some of the experiences of this kind, or can refer to literature, which avoids local minimum in a more effective way than the one used in the "random walk" approach.

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