Path Planning Based on Task Knowledge and User’s Intention
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This paper introduces a method to extract task knowledge from an example shown by an teacher or generated by a planner, and to apply the knowledge to plan a path in similar environments where dimentions, design and location of parts may change. Our goal is to make efficient use of learning task resource and to easily plan a path in complex environments. Our method is based on the A*algorithm. We developed a technique to generate a suboptimal path with much less search nodes than the traditional A*algorithm, and to make a heuristic function that includes task knowledge. Examples are shown to verify the effectiveness of our method.
2012 ◽
Vol 229-231
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pp. 2019-2024
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2021 ◽
Vol 18
(3)
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pp. 172988142110264
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