Parameter Tuning Method to Improve Cycle Time of Soft Robotic Hand System Using Bayesian Optimization

The aim of this study is to improve the cycle time of transport operation by a robotic manipulator equipped with a soft robotic hand. This paper proposes a novel optimization strategy for the manipulator motion that considers the vibration induced in soft robotic hands. Using Bayesian optimization, the manipulator’ motion parameters are optimized through a small number of actual experiments. In the experiments, the cycle time is measured using only a 30-fps camera, resulting in the low-cost parameter tuning system. The proposed method was experimentally evaluated by comparing the result obtained by the proposed method and the grid-search-based tuning method. The obtained cycle times were close to each other, and the proposed method achieved the optimization with 15% of the number of searches in the grid search.