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KCI 후보
운동계획을 위한 입자 군집 최적화를 이용한 시범에 의한 학습의 적응성 향상
Adaptability Improvement of Learning from Demonstration with Particle Swarm Optimization for Motion Planning
김정중 ( Jeong-jung Kim ) , 이주장 ( Ju-jang Lee )
UCI I410-ECN-0102-2019-500-001630279

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.

1. Introduction
2. Combination of Learning from Demonstration and Particle Swarm Optimization
3. Simulations
4. Conclusion
References
[자료제공 : 네이버학술정보]
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