Sampling techniques for probabilistic roadmap planners

Abstract The probabilistic roadmap approach is a commonly used motion planning technique.A crucial ingredient of the approach is a sampling algorithm that samples the configuration space of the moving object for free configurations. Over the past decade manysampling techniques have been proposed. It is difficult to compare the different techniques because they were tested on different types of scenes, using different underlying libraries,implemented by different people on different machines. We compared 12 of such sampling techniques within a single environment on the same scenes. The results were surprising inthe sense that techniques often performed differently than claimed by the designers. The study also showed how difficult it is to evaluate the quality of the techniques. The resultsshould help users in deciding which technique is suitable for their situation