We propose a new approach to robot path planning that consists of building and searching a graph connecting the local minima of a potential function defined over the robot’s configuration space. A planner based on this approach has been implemented. This planner is considerably faster than previous

at integrally related frequencies to achieve motion at a given bracketing level. We define a class of systems which can be steered using sinusoids (chained systems) and give conditions under which a class of two-input systems can be converted into this form. I.

One important goal in robotics is to make it possible for robots to perfonn tasks whose goals are expressed in high-level declarative terms. In this context, researchers in motion planning develop algorithms to automatically generate motions to achieve goals fonnulated as geometric arrangements

Motion planning is a field of growing importance as more and more computer controlled vehicles are being used daily. While some work has been done in this area, much remains, especially in terms of practical efficiency. Complete algorithms exist which will solve virtually any motion planning

Abstract Motion planning in continuous space is a fundamental robotics problem that has been approached from many perspectives. Rapidly-exploring Random Trees (RRTs) use sampling to efficiently traverse the continuous and high-dimensional state space. Heuristic graph search methods use lower bounds

We describe the Open Motion Planning Library (OMPL), a new library for sampling-based motion planning, which contains implementations of many state-of-the-art planning algorithms. The library is designed in a way that allows the user to easily solve a variety of complex motion planning problems

In this paper we study a notion of topological complexity TC(X) for the motion planning problem. TC(X) is a number which measures discontinuity of the process of motion planning in the configuration space X. More precisely, TC(X) is the minimal number k such that there are k different “motion

sensors, safety mechanisms, and general integrated software tools and techniques are needed. We believe that the development of practical motion planning algorithms and obstacle avoidance software for humanoid robots represents an important enabling technology. This paper gives an overview of some of our

Motion planning under gravity for underactuated three-link robots

This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning