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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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Journal ArticleDOI

Fuzzy behaviors for mobile robot navigation: design, coordination and fusion

TL;DR: The architecture is based on regulatory control using fuzzy logic control and the coordination is defined by fuzzy metarules which define the context of applicability for each behavior, and two combination methods for fusing the preferences from each behavior are used.
Proceedings ArticleDOI

Rapid physics-based rough-terrain rover planning with sensor and control uncertainty

TL;DR: A model-based planning method is presented in this paper that is computationally efficient and takes into account uncertainty in the robot model, terrain model, range sensor data, and rover path following errors.
Proceedings ArticleDOI

A general framework for sampling on the medial axis of the free space

TL;DR: A general framework for sampling the configuration space in which randomly generated configurations, free or not, are retracted onto the medial axis of the free space, which provides a template encompassing all possible retraction approaches.
Proceedings ArticleDOI

A tiered planning strategy for biped navigation

TL;DR: A three-tiered planner for biped navigation over large distances through complex environments where conventional 2D planning algorithms designed for wheeled robots fail to find a solution.
Proceedings ArticleDOI

Local incremental planning for nonholonomic mobile robots

TL;DR: This nonholonomic planner employs a direct projection strategy to modify online the output of a holonomic incremental planner, and generates velocity control inputs that realize the desired motion in a least-squares sense.