Planning expected-time optimal paths for target search by robot
Botao Zhang, Shirong Liu · 2012
In this paper, a path planning approach for finding an optimal path is proposed to reduce the expected-time in target search by robot. This approach employs a heuristic algorithm to generate a basic path and minimize the expected-time. Considering different direction may lead to different expected-time in a same loop, a direction choosing method is presented to improve the performance of this heuristic algorithm. Then, based on the improved algorithm, a two-level path planning approach is investigated. At the top level, the improved heuristic algorithm is used to generate a sequence of observation points. At the lower level, the Artificial Potential Field (APF) is employed to plan paths among observation points. Simulations and experiments demonstrated that this approach can reduce the expected time for target search.