Kentaro Kayama

Semi-autonomous outdoor mobility support system for elderly and disabled people

We have been developing the Robotic Communication Terminals (RCTs), which are integrated into a mobility support system to assist elderly or disabled people who suffer from impaired mobility. The RCT system consists of three types of terminals and one server: an environment-embedded terminal, a user-carried mobile terminal, a user-carrying mobile terminal, and a barrier-free map server. The RCT is an integrated system that can be used to cope with various problems of mobility, and provide suitable support to a wide variety of users. This paper provides an in-depth description of the user-carrying mobile terminal. The system itself is a kind of intelligent wheeled vehicle. It can recognize the surrounding 3D environment through infrared sensors, sonar sensors, and a stereo vision system with three cameras, and avoid hazards semi-autonomously. It also can provide adequate navigation by communicating with the geographic information system (GIS) server and detect vehicles appearing from the blind side by communicating with environment-embedded terminals in the real-world.

Construction of elevation map for user-carried outdoor mobile robot using stereo vision

The construction method of environment description using stereo camera is described in this paper. This method is for safety of user-carried semi-autonomous mobile robot in outdoor environment that contains steps and slopes. This method constructs environment map by using three-dimension occupancy grid. These grids are cuboids fine in height direction. Three-dimension flow is used for self-localization. The elevation map is constructed from the three-dimension occupancy grid, and the dangerous area is calculated from the elevation map. This make it enable to distinguish passable slopes and impassable steps. Moreover, this system is equipped for an outdoor semi-autonomous electric scooter and performed in real world.

Detection of People and Tracking Test Bed Using Multiple Sensors

In mobile and ubiquitous computing environments, acquisition of contextual information about a user situation is necessary to provide useful services. Although the definition of user context may change according to the situation or the service used, contextual information about who, where, and when are considered to be essential. We have built a test bed with multiple sensors: floor pressure sensors, RFID (radio frequency identification) tag systems, and cameras, to carry out experiments to detect the positions of users and track their movement. The test bed is described and experimental results are presented. By using the background subtraction method, which is conventional and effective, we found moving objects can be extracted under limited conditions in real time.