3 accepted papers
In this paper, using the Hypercube Diagonal Experiment we first investigate the convergence rates of sampling-based path-planning algorithms in terms of the dimensionnality of the search space. We show that the probability of sampling a point that improves the solution decreases exponentially with…
We present several modifications to the previously proposed MSPP algorithm that can speed-up its execution considerably. The MSPP algorithm leverages a multi-scale representation of the environment in n dimensions encoded in tree structure constructed by recursive dyadic partitioning of the search s…
We present a path-planning algorithm that leverages a multi-scale representation of the environment. The algorithm works in n dimensions. The information of the environment is stored in a tree representing a recursive dyadic partitioning of the search space. The information used by the algorithm is…