4 accepted papers
In this letter, we propose learning-based force control of twisted string actuators (TSAs) using a neural network-based inverse model. A learning-based force controller is designed using the input and output data of TSAs without a dynamic model of TSAs. Furthermore, the neural network-based inverse
A convenient situation can be realized if home robots replace housework. However, tasks in an actual home environment are challenging for robots. Particularly, cleaning the table after eating is challenging because of the cluttered environments and various tableware shapes. This study presents a new…
This letter proposes a design method of a compact embedded hydraulic power unit (HPU) for a bipedal robot and a controller to regulate the supply pressure. The HPU consists of an integrated pump-motor unit. The unit is immersed in hydraulic oil for efficient space utilization and heat dissipation fr
In this study, a learning-based force controller for a hydraulic actuator is presented. We propose a control method with an inverse model composed of a deep neural network, which accurately tracks a force trajectory. This learning-based controller can be trained offline using force and position data