Proceedings Article10.1109/IROS.2009.5354185
Adaptive node sampling method for probabilistic roadmap planners
Byungjae Park,Wan Kyun Chung +1 more
- 10 Oct 2009
- pp 4399-4405
TL;DR: The proposed adaptive node sampling method substitutes the random sampling in the learning phase of the PRM planner and improves the configuration of the roadmap and finds out efficient paths even in narrow passages.
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Abstract: This paper proposes an adaptive node sampling method for the probabilistic roadmap (PRM) planner. The proposed method substitutes the random sampling in the learning phase of the PRM planner and improves the configuration of the roadmap. This method uses two phase to determine nodes in order to construct the roadmap. First, the proposed method extracts initial nodes using the approximated cell decomposition and the Harris corner detector. Second, the positions of these nodes are optimized using a construction process of the centroidal voronoi tessellation (CVT). The proposed method determines the adequate number and positions of the nodes to represent the entire free space, and the PRM planner based on the proposed method finds out efficient paths even in narrow passages. These properties have been verified though experiments.
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Citations
Roadmap Coverage Improvement Using a Node Rearrangement Method for Mobile Robot Path Planning
TL;DR: The mobile robot path planner using the proposed rearranged roadmap was integrated with a local planner that considers the kinematic properties of a mobile robot, and the efficiency and the safety of the paths were verified by simulation.
5
Path Planning and Control of an Autonomous Quadrotor Testbed in a Cluttered Environment
Trevor W. Caplinger
- 01 Jan 2015
TL;DR: This work shows a review of selected algorithms, and two of these are selected for simulation and testing using a quadrotor unmanned aerial vehicle (UAV) in a dynamic indoor environment which requires replanning capabilities.
•Dissertation
Using trails to improve map generation for virtual agents in large scale, online environments
Katrina Samperi
- 01 Jul 2016
TL;DR: It is found that trails in a virtual environments are a useful source of information for an agent's map building process, and can be used to improve rapidly exploring randomised tree and probabilistic roadmap generation, as well as being used as a source of Information for segmenting maps in very large scale environments.
2
Path reconstruction method for sampling based planners
Byungjae Park,Jinwoo Choi,Wan Kyun Chung +2 more
- 01 Oct 2010
TL;DR: The node update and Dijkstra's graph search algorithm are used in the iterative process of the proposed path reconstruction method and can be applied to any kinds of sampling based planners if the planned path represented by a simple path graph.
2
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