A Reactive Lazy PRM Approach for Nonholonomic Motion Planning

Lazy Toggle PRM: An Efficient Motion Planning Strategy for Task Sequences

Probabilistic RoadMaps (PRMs) are quite successful in solving complex and high-dimensional motion planning problems. While particularly suited for multiple-query scenarios and expansive spaces, they lack efficiency in both solving a small number of queries in an environment and mapping narrow spaces. Two PRM variants separately tackle these gaps. Lazy PRM reduces the computational cost of roadm...

Randomized motion planning for car-like robots with C-PRM

In this work, we propose a new approach for motion planning for nonholonomic car-like robots which is based on a Customizable PRM (C-PRM). A major advantage of our approach is that it enables the same roadmap to be efficiently utilized for car-like robots with different turning radii, which need not be known before query time. Our C-PRM-based approach first builds a so-called control roadmap wh...

Path Planning Using Lazy PRM

A smoothing strategy for prm paths: application to 6-axes motoman manipulator

This paper describes the use of the probabilistic motion planning technique SBL “Single-Query Bidirectional Probabilistic Algorithm with Lazy Collision Checking” or in motion planning for robot manipulators. We present a novel strategy to remedy the PRM “Probabilistic Roadmap” paths which are both excessively long and velocity discontinuous. The optimization of the path will be done first throu...

Quasi-Randomized Path Planning

We propose the use of quasi-random sampling techniques for path planning in high-dimensional conng-uration spaces. Following similar trends from related numerical computation elds, we show several advantages ooered by these techniques in comparison to random sampling. Our ideas are evaluated in the context of the probabilistic roadmap (PRM) framework. Two quasi-random variants of PRM-based plan...