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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.read more
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Journal ArticleDOI
An Adaptive Guidance System for Robotic Walking Aids
TL;DR: A new adaptive guidance system for robotic walkers has been developed that is able to lead the walking aid user to a given target while considering his inputs during guidance and adapting the path respectively.
Proceedings ArticleDOI
Motion planning for a crowd of robots
Tsai-Yen Li,Hsu-Chi Chou +1 more
TL;DR: This paper proposes an efficient centralized planner that is much faster than the traditional randomized planning approaches and uses a hierarchical sphere tree structure to group robots dynamically.
Journal ArticleDOI
A biologically inspired neural net for trajectory formation and obstacle avoidance
TL;DR: A biologically inspired two-layered neural network for trajectory formation and obstacle avoidance that is able to reach a target even in the presence of an external perturbation.
Journal ArticleDOI
Integration of task scheduling, action planning, and control in robotic manufacturing systems
M. Song,Tzyh-Jong Tarn,N. Xi +2 more
TL;DR: In this paper, a novel approach for solving a challenging problem in the intelligent control of robotic manufacturing systems, i.e., the integration of lowlevel system sensing and control with high-level system behavior and perception, is presented.
Journal ArticleDOI
Imagination and situated cognition
TL;DR: In this paper, the authors describe an agent architecture based on the idea that cognition is imagined interaction, i.e. that cognitive tasks are performed by interacting with an imaginary world, and demonstrate the architecture by its application to a subsumption-based mobile robot.