ベイズ最適化を用いた投擲マニピュレーション

抄録

This paper propose the learning scheme for a throwing manipulation on a 2-D workspace with the 1-DOF robotic arm and verifies its validity experimentally. The proposed learning scheme consists of Bayesian optimization and sequential quadratic programming. The proposed learning scheme is able to make the positioning error less than 0.7mm after 11 trials.