Yukihiko Kitano

A novel visible light communication system for enhanced control of autonomous delivery robots in a hospital

Control systems for Autonomous mobile delivery robots have been described before. However, the control they provide is limited, leaving potential for serious errors. The current mobile robot systems concentrate on position accuracy and operational function but leave open management of safety hazards such as entering the dangerous and not intended areas as stairway. In order to increase the safety of the robot, it is as important to work with sensors installed in the external environment as the sensors installed on the robot. For this purpose, visible light communication (VLC) is a promising device to be used with the robot system. VLC creates an in-house GPS system by installing special LED lights that can replace standard lighting in key locations in the hospital. We have developed an in-hospital transportation robot, called HOSPI in which the control system has been enhanced by combining the navigational sensors of the robot and a VLC using installed lighting in the building. By using VLC, robots can obtain more information about the environment. As the first step for the practical application of VLC to robot system, we use VLC to overcome problems in conventional localization approaches, and to provide an additional line of defense in the case of catastrophic failures. This paper also describes experimental and actual operational results in detail of robots equipped, in an actual hospital, with the described process.

Recognition of 3D dynamic environments for mobile robot by selective memory intake and release of data from 2D sensors

We have developed an autonomous mobile robot to perform in-hospital transportation. When an autonomous mobile robot moves in a hospital, it needs to detect and avoid such obstacles as beds, wheelchairs, patients, visitors, and hospital staff. These obstacles move and often have overhanging parts that cannot be detected by only 2D sensor which measures horizontal surface. The robot, therefore, must recognize obstacles in a three-dimensional space on a real-time basis. Appropriate and practical 3D sensors for actual use are not available, and 3D recognitions using 2D sensors such as 3D-SLAM are not fast enough to collide with moving object. This paper proposes a method that recognizes the three-dimensional environment around a mobile robot using a laser range finder at its front for measuring the horizontal surface and three additional range finders at the left and right sides and the front top position to look down and detect three-dimensional obstacles. The information is integrated by data fusion into the memory. The features of this method include memorization of the obstacle positions with overhangs and removing the memorized position of the moving obstacles from the memory by selective memory intake and release of data from 2D sensors. This paper also describes experimental and actual operational results in detail about the robot equipped with the developed process in real hospital.