This paper explores the use of robots to autonomously assemble parts with variations in
colors and textures. Specifically, we focus on peg-in-hole assembly with some initial position …

Imitation learning has been studied as an efficient and high-performance method to
generate robot motion. Specifically, bilateral control-based imitation learning has been …

We propose a deep learning based method for fast and responsive human-robot handovers
that generate robot motion according to human motion observations. Our method learns an …

Thegeneration of robot motions in the real world is difficult by using conventional controllers
alone and requires highly intelligent processing. In this regard, learning-based motion …

Recent research in the field of robotics has primarily focused on motion generation methods
using imitation learning to adapt to various environments. Human-level speed motion can be …

Regolith sampling is one of the core missions in deep space exploration. The design,
optimization, and fabrication of samplers are challenging tasks to meet the requirements of …

Aiming at the problem of 3D point cloud noise affecting the efficiency and precision of
human body 3D reconstruction in complex scenes, a 3D point cloud registration denoising …

Machine learning is now playing important role in robotic object manipulation. In addition,
force control is necessary for manipulating various objects to achieve robustness against …

A technique named Learning from Demonstration allows robots to learn actions in a human
living environment from the demonstrations directly. In a learning method from …

Robots' acceptability among humans and their sociability can be significantly enhanced by
incorporating human-like reactions. Humans can react to environmental events very quickly …