Path Planning Based on Task Knowledge and User’s Intention
Hiroyuki Ogata* and Tomoichi Takahashi**
* Nippon Telegraph and Telephone Co., 3-9-11 Midori-cho, Musashino-shi, Tokyo, 180 Japan
**Chubu University 1200 Matsumoto, Kasugai-shi, Aichi, 487 Japan (This study was done in NTT Co.)
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.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.