Kohsei Matsumoto

Self-calibration of environmental camera for mobile robot navigation

An environmental camera is a camera embedded in a working environment to provide vision guidance to a mobile robot. In the setup of such robot systems, the relative position and orientation between the mobile robot and the environmental camera are parameters that must unavoidably be calibrated. Traditionally, because the configuration of the robot system is task-driven, these kinds of external parameters of the camera are measured separately and should be measured each time a task is to be performed. In this paper, a method is proposed for the robot system in which calibration of the environmental camera is rendered by the robot system itself on the spot after a system is set up. Specific kinds of motion patterns of the mobile robot, which are called test motions, have been explored for calibration. The calibration approach is based upon executing certain selected test motions on the mobile robot and then using the camera to observe the robot. According to a comparison of odometry and sensing data, the external parameters of the camera can be calibrated. Furthermore, an evaluation index (virtual sensing error) has been developed for the selection and optimization of test motions to obtain good calibration performance. All the test motion patterns are computed offline in advance and saved in a database, which greatly shorten the calibration time. Simulations and experiments verified the effectiveness of the proposed method.

Multiple camera image interface for operating mobile robot

This paper describes a human-robot interface for operating a mobile robot using multiple images provided by cameras distributed throughout locations. In a case that a human operates the robot recognizing wide working area with multi-displayed images, the image display method for human will be an important subject. To assist human recognition of the relationship between multi-displayed images from cam- eras located throughout wider unknown work areas, we designed the interface to have the following main features: 1) indication of overlap areas from cam- eras to support human recognition of working areas, 2) indication of rough routes for robot navigation to assist robot operation from captured images. Our experiments revealed the effectiveness of our interface and that of the whole robot system.

Camera calibrationless vision calibration for transfer robot system

This research was focused on a system in which a manipulator with robot vision transfers objects to a mobile robot that moves on a flat floor. In this system, an end effector of a manipulator operates on a plane surface, so only single vision is required. In a robot vision system, many processes are usually needed for vision calibration, and one of them is measurement of camera parameters. We developed a calibration technique that does not explicitly require camera parameters to reduce the number of calibration processes required for our researched system. With this technique, we measured relations between coordinate systems of images and a mobile robot in the moving plane by using a projective transformation framework. We also measured relations between images and the manipulator in an arbitrary plane in the same way. By analyzing the results, we obtained a relation between the mobile robot and the manipulator without explicitly calculating the camera parameters. This means capturing images of the calibration board can be skipped. We tested the calibration technique using an object-transfer task. The results showed the technique has sufficient accuracy to achieve the task.