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Robot Motion Planning
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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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Proceedings ArticleDOI
MAPRM: a probabilistic roadmap planner with sampling on the medial axis of the free space
TL;DR: A new method of sampling the configuration space in which randomly generated configurations are retracted onto the medial axis of the free space is proposed, and it is shown that sampling and retracting in this manner increases the number of nodes found in small volume corridors in a way that is independent of the volume of the corridor and depends only on the characteristics of the obstacles bounding it.
Proceedings ArticleDOI
Virtual voyage: interactive navigation in the human colon
TL;DR: This work presents an interactive virtual colonoscopy method, which uses a physicallybased camera control model and a hardware-assisted visibility algorithm that culls invisible regions based on their visibility through a chain of portals, thus providing interactive rendering speed.
Journal IssueDOI
Differentially constrained mobile robot motion planning in state lattices
TL;DR: Experimental results with research prototype rovers demonstrate that the planner allows the entire envelope of vehicle maneuverability in rough terrain, while featuring real-time performance.
Journal ArticleDOI
An Autonomous Robot for Harvesting Cucumbers in Greenhouses
E.J. van Henten,Jochen Hemming,B.A.J. van Tuijl,J.G. Kornet,J. Meuleman,Jan Bontsema,E.A. van Os +6 more
TL;DR: This paper describes the concept of an autonomous robot for harvesting cucumbers in greenhouses and describes the individual hardware and software components of the robot, which include the autonomous vehicle, the manipulator, the end-effector, the two computer vision systems for detection and 3D imaging of the fruit and the environment and a control scheme that generates collision-free motions for the manipulators during harvesting.
Proceedings ArticleDOI
Optimal kinodynamic motion planning using incremental sampling-based methods
Sertac Karaman,Emilio Frazzoli +1 more
TL;DR: In this article, the RRT* algorithm is extended to deal with differential constraints and a sufficient condition for asymptotic optimality is provided, which ensures almost sure convergence of the solution returned by the algorithm to an optimal solution, while maintaining the same properties of the standard RRT algorithm, both in terms of computation of feasible solutions and of computational complexity.