Cable route planning in complex environments using constrained sampling

Abstract

We present a route planning algorithm for cable and wire layouts in complex environments. Our algorithm precomputes a global roadmap of the environment by using a variant of the probabilistic roadmap method (PRM) and performs constrained sampling near the contact space. Given the initial and the final configurations, we compute an approximate path using the initial roadmap generated on the contact space. We refine the approximate path by performing constrained sampling and use adaptive forward dynamics to compute a penetration-free path. Our algorithm takes into account geometric constraints like non-penetration and physical constraints like multi-body dynamics and joint limits. We highlight the performance of our planner on different scenarios of varying complexity.