Published in

World Scientific Publishing, International Journal on Artificial Intelligence Tools, 06(18), p. 949-957, 2009

DOI: 10.1142/s0218213009000470

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A New Parameterized Potential Family for Path Planning Algorithms

Journal article published in 2009 by Fabricio Ferrari ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

In this work, it is proposed a new family of potentials for path planning algorithms, one kind to the goal and other to the obstacles. With these new potentials it is possible to parameterize the potential scale length and strength easily, providing better control over the moving object path characteristics. In this way, the path problem can be treated analytically. For example, the minimum distance between the moving object and the obstacles can be calculated as a function of the potential parameters. Simulations are made to test its ability to guide a vehicle through an obstacle-free path towards the goal. The success rate of the moving object on reaching the goal is compared with the potential parameters and with obstacle configuration and distribution parameters.

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