Iterative Solution for the Narrow Passage Problem in Motion Planning

Finding a path in a narrow passage is a bottleneck for randomised sampling-based motion planning methods. This paper introduces a technique that solves this problem. The main inspiration was the method of exit areas for cavities in protein models, but the proposed solution can also be used in another context. For data with narrow passages, the proposed method finds passageways for which sampling-based methods are not sufficient, or provides information that a collision-free path does not exist. With such information, it is possible to quit the motion planning computation if no solution exists and its further search would be a loss of time. Otherwise, the method continues to sample the space with sampling-based method (a RRT algorithm) until a solution is found or the maximum number of iterations is reached. The method was tested on real biomolecular data - dcp protein - and on artificial data (to show the superiority of the proposed solution on better-imagined data) with positive results.