This paper proposes a vibrotactile glove interface that enabled users to perceive tactile sensations of virtual objects. The proposed vibrotactile interface was designed to be easy-to-use, easily portable, and lightweight. Active touch might also be useful to realize informative tactile communication. To provide tactile stimuli based on movement of the fingers, five bending sensors were installed on the glove. In this study, the relationship of the correspondence between vibrotactile stimuli and tactile mental imagery was investigated. Subjects' mental impressions of vibrotactile stimuli were measured by using the semantic differential (SD) method. Distinctive imagery from subjects' answers was extracted for factor analysis. After that, a vibration stimuli model was applied to active touch. The tactile mental imagery of users was evaluated for both passive and active touches.

In an increasing demand for human-robot collaboration systems, the need for safe robots is crucial. This paper presents a proactive strategy to enable an awareness of the current risk for the robot. The awareness is based upon a map of historically occupied space by the operator. The map is built based on a risk evaluation of each pose presented by the operator. The risk evaluation results in a risk field that can be used to evaluate the risk of a collaborative task. Based on this risk field, a control algorithm that constantly reduces the current risk within its task constraints was developed. Kinematic redundancy was exploited for simultaneous task performance within task constraints, and risk minimization. Sphere-based geometric models were used both for the human and robot. The strategy was tested in simulation, and implemented and experimentally tested on a NACHI MR20 7-axes industrial robot

This study proposes an indoor movable static object extraction approach for building environmental maps that describe indoor human activities. In particular, it is essential to distinguishing people from non-human movable objects. To address this issue, we classify static objects into three categories based on their features. Methods for extracting movable static objects using each feature are presented. We conducted experiments and confirmed that the movable static objects were successfully detected and redefined as backgrounds, and only people were determined as dynamic objects. GRAPHICAL ABSTRACT

To maintain long-term human-robot communication, a robot behavior model based on the behaviors of dogs in human-dog relationships has been proposed. We apply this model to a robot in a monitoring support system designed for home care. This paper presents an improvement to the model, adding behavioral factors to show different characteristics of the behaviors. We conduct experiments to evaluate users' impressions of the robot behaviors when given different characteristics using a simulator. Our findings show that the subjects had the impressions that we expected based on the factors selected.

The work requiring a heavy load like welding should be automated. However, it is difficult to fully automate tasks requiring complexity and high quality, such as the welding of Francis hydro power turbines. It is therefore necessary for people to be involved in such tasks. Introducing Human-in-the-loop system makes it possible to combine robot productivity and human flexibility, and to build a system that is compatible with high productivity and quality. When the welding operation is performed by remote operation, the worker grasps the state of the robot from the monitor. However, it is difficult to fully understand the movement of the robot only with visual information from the monitor. In this paper, to improve the workability, we grasp the behavior of the robot when taking over work from a robot to operator in a welding task, and present pose information of the end effector to the operator using vibrotactile information. We evaluated the designed vibrotactile stimulus and confirmed its usefulness.