Reachability-based analysis for Probabilistic Roadmap planners

Reachability-based analysis for Probabilistic Roadmap planners

In the last fifteen years, sampling-based planners like the Probabilistic Roadmap Method (PRM) have proved to be successful in solving complex motion planning problems. While theoretically, the complexity of the motion planning problem is exponential in the number of degrees of freedom, sampling-based planners can successfully handle this curse of dimensionality in practice. We give a reachabil...

Gaussian Sampling for Probabilistic Roadmap Planners

Sampling Techniques for Probabilistic Roadmap Planners

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 many sampling techniques have been proposed. It is difficult to compare the different techniques because they were tested on different types of scenes,...

A Comparative Study of Probabilistic Roadmap Planners

The probabilistic roadmap approach is one of the leading motion planning techniques. Over the past eight years the technique has been studied by many different researchers. This has led to a large number of variants of the approach, each with its own merits. It is difficult to compare the different techniques because they were tested on different types of scenes, using different underlying libr...

The Gaussian Sampling Strategy for Probabilistic Roadmap Planners

Probabilistic roadmap planners (PRMs) form a relatively new technique for motion planning that has shown great potential. A critical aspect of PRM is the probabilistic strategy used to sample the free configuration space. In this paper we present a new, sample sampling strategy, which we call the Gaussian sampler, that gives a much better coverage of the dificult parts of the free Configuration...