A comparison of sampling-based path planners for a grape vine pruning robot arm

Abstract

We compare eight commonly used path planning algorithms on a robot arm for pruning grape vines. Pruning grape vines involves planning a path that reaches into cluttered regions and through narrow passages. These problems are known to be difficult for sampling based planners. We show that the choice of milestone expansion method has more of an effect on path planner performance than search directionality or laziness. We found the Rapidly Expanding Random Trees algorithm and its variations had the best overall performance.