OSIS: Obstacle-Sensitive and Initial-Solution-first path planning

The efficiency of informed path planning algorithms is contingent upon how quickly the planner can find the initial solution and the associated overhead involved in collision detection. Existing informed planners do not fully exploit the information contained in historical collision detection results, resulting in additional unnecessary collision detections. Furthermore, they optimize paths through rewiring before discovering an initial solution, which not only hampers the planner’s space exploration, but also generates a superfluous amount of unproductive over-head. To address the shortcomings of existing algorithms, this paper proposes an Obstacle-Sensitive and Initial-Solution-first path planning algorithm (OSIS). OSIS uses historical collision detection results to predict the distribution of obstacles in space and utilizes an initial-solution-first path optimization strategy to avoid useless path optimization. Experiments show that OSIS can efficiently bypass obstacles and converge the cost of the solution compared to existing algorithms.