3 accepted papers
In-hand manipulation has attracted attention because of its potential for performing dexterous manipulation tasks. Few successful examples using real robotic fingers have been reported because model-based approaches have been assumed. A gradient descent-based iterative learning control is one of the…
In this study, we propose a novel iterative learning scheme, which generates time-series data comprising the impedance value for human-robot cooperative work, where the human operator moves the end-effector from an initial position to a goal position. The proposed learning scheme iteratively updates…
This paper proposes an iterative learning control scheme for whole-arm object manipulation by using a robotic hand system composed of a velocity-controlled finger and a torque-controlled finger. The novel iterative learning control scheme consists of the PD-type iterative learning control scheme for…