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Robot Motion Planning

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TLDR
This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.
Abstract
1 Introduction and Overview.- 2 Configuration Space of a Rigid Object.- 3 Obstacles in Configuration Space.- 4 Roadmap Methods.- 5 Exact Cell Decomposition.- 6 Approximate Cell Decomposition.- 7 Potential Field Methods.- 8 Multiple Moving Objects.- 9 Kinematic Constraints.- 10 Dealing with Uncertainty.- 11 Movable Objects.- Prospects.- Appendix A Basic Mathematics.- Appendix B Computational Complexity.- Appendix C Graph Searching.- Appendix D Sweep-Line Algorithm.- References.

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Proceedings ArticleDOI

Analysis of probabilistic roadmaps for path planning

TL;DR: This work provides an analysis of a path planning method which uses probabilistic roadmaps and provides estimates for N, the principal parameter of the method, in order to achieve failure probability within prescribed bounds.
Journal ArticleDOI

Navigation Strategies for Exploring Indoor Environments

TL;DR: The concept of a safe region is introduced, defined as the largest region that is guaranteed to be free of obstacles given the sensor readings made so far, and an NBV algorithm is proposed that uses the safe-region concept to select the next robot position at each step.
Journal ArticleDOI

Nearness diagram (ND) navigation: collision avoidance in troublesome scenarios

TL;DR: The design of a reactive navigation method that uses a "divide and conquer" strategy based on situations to simplify the difficulty of the navigation is described, leading to new reactive methods that must be able to navigate in arduous environments.
Book ChapterDOI

Coverage Path Planning: The Boustrophedon Cellular Decomposition

TL;DR: The boustrophedon cellular decomposition is developed, which is an exact cel­ lular decomposition approach, for the purposes of coverage, and is provably complete and Experiments on a mobile robot validate this approach.
Journal ArticleDOI

Robot Collisions: A Survey on Detection, Isolation, and Identification

TL;DR: This survey paper review, extend, compare, and evaluate experimentally model-based algorithms for real-time collision detection, isolation, and identification that use only proprioceptive sensors that cover the context-independent phases of the collision event pipeline for robots interacting with the environment.