Robots are expected to replace menial tasks such as housework. Some of these tasks
include nonprehensile manipulation performed without gras** objects. Nonprehensile …

Recently, motion generation by machine learning has been actively researched to automate
various tasks. Imitation learning is one such method that learns motions from data collected …

We have developed an autonomous robot motion generation model based on distributed
and integrated multimodal learning. Since each modality used as a robot's senses, such as …

There has been an increasing demand for housework robots to handle various objects. It is,
however, difficult to achieve object-shape-oriented tasks in conventional research owing to …

We propose a tool-use model that enables a robot to act toward a provided goal. It is
important to consider features of the four factors; tools, objects actions, and effects at the …

Safe physical human-robot collaboration is possible with soft robots due to their inherent
compliance and low inertia. Soft bodies inherently possess passive compliance, providing …

Robots are expected to manipulate objects in a safe and dexterous way. For example,
washing dishes is a dexterous operation that involves scrubbing the dishes with a sponge …

In this article, we present a feedback control method for tactile coverage tasks such as
cleaning or surface inspection. Although these tasks are challenging to plan due to the …

A versatile robot working in a domestic environment based on a deep neural network (DNN)
is currently attracting attention. One of the roles expected for domestic robots is caregiving …

We propose a motion generation model for simultaneous control of motion and force using
deep learning. Conventional force control methods require expensive torque sensors and …