DOI: 10.5176/2251-2179_ATAI12.29
Authors: Angie Shia, Haim Schweitzer
Abstract: Collision avoidance of moving systems is a well studied problem. The use of an Artificial Potential Field function is a popular approaches to compute in real time a path that avoids collision between agents.
It involves the minimization of a weighted sum of an attractive force and a repulsive force. Previous studies
consider these weights to be fixed design parameters, to be determined experimentally. In particular, these parameters
do not change during the run of the algorithm. Our main result is based on the observation that by
dynamically changing these parameters one can obtain a guarantee on a minimum safety distance between the
agents. Specifically, if the agents compute their path by minimizing the potential field with properly chosen
weights, there will always be a guaranteed safety distance between each pair of agents. We describe promising
experimental results, where the minimization is obtained by applying steepest descent to the potential function.
Our simulation validates our model and demonstrated its effectiveness for a group of non-cooperative agents
moving in a small area.
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