Proceedings ArticleDOI
Randomized preprocessing of configuration for fast path planning
Lydia E. Kavraki,Jean-Claude Latombe +1 more
- pp 2138-2145
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This paper presents a new approach to path planning for robots with many degrees of freedom (DOF) operating in known static environments that is particularly attractive for many-DOF robots which have to perform many successive point-to-point motions in the same environment.Abstract:
This paper presents a new approach to path planning for robots with many degrees of freedom (DOF) operating in known static environments. The approach consists of a preprocessing and a planning stage. Preprocessing, which is done only once for a given environment, generates a network of randomly, but properly selected, collision-free configurations (nodes). Planning then connects any given initial and final configurations of the robot to two nodes of the network and computes a path through the network between these two nodes. Experiments show that after paying the preprocessing cost (on the order of hundreds of seconds), planning is extremely fast (on the order of a fraction of a second for many difficult examples involving a 10-DOF robot). The approach is particularly attractive for many-DOF robots which have to perform many successive point-to-point motions in the same environment. >read more
Citations
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Journal ArticleDOI
Probabilistic roadmaps for path planning in high-dimensional configuration spaces
TL;DR: Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (/spl ap/150 MIPS), after learning for relatively short periods of time (a few dozen seconds).
Journal ArticleDOI
Sampling-based algorithms for optimal motion planning
Sertac Karaman,Emilio Frazzoli +1 more
TL;DR: In this paper, the authors studied the asymptotic behavior of the cost of the solution returned by stochastic sampling-based path planning algorithms as the number of samples increases.
Proceedings ArticleDOI
RRT-connect: An efficient approach to single-query path planning
TL;DR: A simple and efficient randomized algorithm is presented for solving single-query path planning problems in high-dimensional configuration spaces by incrementally building two rapidly-exploring random trees rooted at the start and the goal configurations.
Posted Content
Sampling-based Algorithms for Optimal Motion Planning
Sertac Karaman,Emilio Frazzoli +1 more
TL;DR: The main contribution of the paper is the introduction of new algorithms, namely, PRM and RRT*, which are provably asymptotically optimal, i.e. such that the cost of the returned solution converges almost surely to the optimum.
Journal ArticleDOI
Learning metric-topological maps for indoor mobile robot navigation
TL;DR: This paper describes an approach that integrates both paradigms: grid-based and topological, which gains advantages from both worlds: accuracy/consistency and efficiency.
References
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Book
Robot Motion Planning
TL;DR: This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.
Journal ArticleDOI
Probabilistic roadmaps for path planning in high-dimensional configuration spaces
TL;DR: Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (/spl ap/150 MIPS), after learning for relatively short periods of time (a few dozen seconds).
Journal ArticleDOI
Robot motion planning: a distributed representation approach
TL;DR: 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 is proposed and a planner based on this approach has been implemented.
Journal ArticleDOI
Numerical potential field techniques for robot path planning
TL;DR: The authors investigate a path planning approach that consists of concurrently building and searching a graph connecting the local minima of a numerical potential field defined over the robot's configuration space.
Journal ArticleDOI
A potential field approach to path planning
Y.K. Hwang,Narendra Ahuja +1 more
TL;DR: A path-planning algorithm for the classical mover's problem in three dimensions using a potential field representation of obstacles is presented and solves a much wider class of problems than other heuristic algorithms and at the same time runs much faster than exact algorithms.