This study proposes a robotic massage system combining visual and tactile inspection for personalized therapy. Equipped with RGB-D cameras, a robot arm, and a force sensor, the system identifies massage areas based on body type via skeleton tracking. Using the kneading exploration method, muscle knots are localized efficiently, reducing location errors by up to 85.7% compared to conventional methods. The system also leverages VR visualization, showing massage actions through a robot arm and human-like therapist avatars. A study with ten participants found that human-like avatars, particularly a boy avatar, received higher ratings for pleasantness than a robot arm visualization, while pain perception showed no significant differences. These results highlight the influence of visual representation on psychological evaluations, enhancing the user experience. Future work will focus on improving interaction methods and integrating advanced physiological feedback to develop an adaptive Human-Robot Interaction system for physical and psychological care.

This study addresses congestion caused by dense populations, promoting safe, efficient, and comfortable mobility in sustainable societies. It focuses on mobile robots for crowd management, proposing a novel method using Flow-Robot Interaction (FRI) and a heuristic behavior-based Social Force Model (SFM) to dynamically control pedestrian overtaking flows. Robots are strategically positioned at overtaking points to interact effectively with pedestrians, restricting paths and minimizing trajectory disruptions. Unlike fixed obstacles, the robots can flexibly reposition to obstruct pedestrians in their desired direction. Simulations show that placing robots at overtaking points stabilizes flows and reduces trajectory changes. Real-world experiments with 11 participants validate these findings, showing alignment of flow velocity with slower pedestrians and prevention of flow expansion. Results demonstrate the potential of human-robot interaction to mitigate congestion, stabilize flows, and enhance mobility. This scalable method offers an effective solution for managing crowds in sustainable urban environments.

It is important for robots to learn the usage of tools and support humans in aging societies. It is expected for robots possible to imitate human skills of tool manipulation properly using a deep neural network, although a huge amount of training data may be required. In this paper, a target human-like task of cleaning dust using several types of brooms with a robot arm is considered. A learning system that can reduce the amount of training data is proposed. The novelty of the proposed system is the ability to estimate the initial parameters of a deep neural network based on the shape of the broom and data stored from previous experience. Furthermore, the system changes the number of learning layers in the deep neural network depending on the broom shape. Results of experiences show the effectiveness in reducing the amount of training data.

Massage therapy is crucial in the field of physical activities and sports to recover muscle fatigue and reduce stress. However, the physical workload on massage therapists is demanding, and the number of therapists is limited. To solve these problems, a massage robot that can move with human-like flexibility and delicacy was develop using a five-fingered robotic hand that mimicking a human hand. Moreover, the aim of this research is to develop a method of online estimation of a user's fatigue based on the muscle hardness in order to evaluate the effect of massaging from tactile information of the robot hand finger-tips to perform appropriate treatment. In this paper, we constructed a system about to measure muscle hardness based on reaction forces and measuring changes in muscle hardness and subjective fatigue over time before and after exercise. Then, the experiment of measuring muscle fatigue was conducted. As a result, the correlation coefficient between changes in muscle hardness and subjective fatigue highly correlated with five of the seven experimental participants. The result suggests the possibility that changes in the reaction force of muscles can be used as a measure for muscle fatigue recovery.

Mobile robot positioning in an indoor environment via fingerprinting technique is made by matching the unknown WiFi data to a spatial WiFi power map database. In past years, this technique has gained reasonable accuracies in the cost of high labor yielded for the database. Thus, automatic database construction by means of interpolating missing data is desired. This paper described a variation of Inverse Distance Weight (IDW) interpolation which is the Modified Shepard's Method (MSM) for our medical-oriented mobile robot - Terapio. By properly selecting the reference locations, we found that this method is better than the conventional IDW method and comparable to the recently popular Kriging interpolation algorithm in an indoor environment by employing the state-of-the-art WKNN positioning algorithm.

We have developed a new type of robot which accompanies the healthcare professionals making medical rounds in patient's bedrooms at hospitals. This novel robot mainly executes two tasks: the carrying armamentarium of round medical supplies and the recording electronic health data on rounds. An omni-directional mobile mechanism and a human tracking control system to follow a specified medical professionals realize smooth transfer movement from the nurses' station to patient's bedroom. Electronic health data on rounds is automatically recorded by using a CCD camera and a voice recorder. When the robot is connected via a cable to a medical data server in nurses' station, the robot transmits the patients' data to the server and receives new patients' information.

We demonstrate a virtual face of a robot with minimum humanity. The name of the robot is “shugo-robot”, which is after “shugo-rei (guardian spirit)“. The shugo-robot follows her/his master by using laser sensors, and takes greeting behaviors by gazing to master's friend and others. Thus, he/she is a communication agent on behalf of master. The head part of the robot has a camera, and finds human faces. Then, the robot's face gazes at a person nearest to the robot. This behavior makes users to believe the robot has an intention to communicate with them. The robot makes blinking at random timings to show the robot is alive, and several facial expressions to show her/his feelings.