Informed Sampling for Asymptotically Optimal Path Planning
نویسندگان
چکیده
منابع مشابه
Informed Sampling for Asymptotically Optimal Path Planning
Anytime almost-surely asymptotically optimal planners, such as RRT*, incrementally find paths to every state in the search domain. This is inefficient once an initial solution is found as then only states that can provide a better solution need to be considered. Exact knowledge of these states requires solving the problem but can be approximated with heuristics. This paper formally defines thes...
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Asymptotically-optimal motion planners such as RRT* have been shown to incrementally approximate the shortest path between start and goal states. Once an initial solution is found, their performance can be dramatically improved by restricting subsequent samples to regions of the state space that can potentially improve the current solution. When the motion planning problem lies in a Euclidean s...
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ژورنال
عنوان ژورنال: IEEE Transactions on Robotics
سال: 2018
ISSN: 1552-3098,1941-0468
DOI: 10.1109/tro.2018.2830331