운동계획을 위한 입자 군집 최적화를 이용한시범에 의한 학습의 적응성 향상 Adaptability Improvement of Learning from Demonstration with Particle Swarm Optimization for Motion Planning

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We present a method for improving adaptability of Learning from Demonstration (LfD) strategy by combining the LfD and Particle Swarm Optimization (PSO). A trajectory generated from an LfD is modified with PSO by minimizing a fitness function that considers constraints. Finally, the final trajectory is suitable for a task and adapted for constraints. The effectiveness of the method is shown with a target reaching task with a manipulator in three-dimensional space.
Publisher
한국산업융합학회
Issue Date
2016-12
Language
Korean
Keywords

Motion planning; Particle swarm optimization; Learning; Manipulator

Citation

한국산업융합학회논문집, v.19, no.4, pp.167 - 175

ISSN
1226-833x
URI
http://hdl.handle.net/10203/223135
Appears in Collection
EE-Journal Papers(저널논문)
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