This paper proposes an accurate self-localization method for a mobile robot. The position of the robot mounted a pan-tilt camera is estimated from the images taken by the camera. In conventional self-localization methods using a stable camera, the detection error of landmark positions on the image was a big problem. Then, we focus on the landmark trajectory on the sequential images which are taken by rotating the pan-tilt camera. By fitting a curve to the trajectory points, the more accurate positions of the landmarks can be obtained than using the multiple images taken by the stable camera. In addition, there is a problem of the landmark displacement on the image due to the tilts of the camera rotation axes. In order to solve this problem, the method for calibrating the tilts using the landmark trajectories is proposed. Our proposed methods are validated for the accurate self-localization in the experiments using the artificial data and the real images taken by the pan-tilt camera.
This paper proposes a novel iterative learning control method for Hamiltonian control systems which can solve a class of optimal control problems. First of all, a symmetric property of the input-output mappings of Hamiltonian systems is clarified which plays an important role in solving, optimal control problems by gradient method. A concrete learning algorithm is derived for mechanical systems possibly with input saturation. Furthermore, numerical simulations of a 2 link robot manipulator demonstrate the the effectiveness of the proposed method.
Particle tracking technology is one of the most promising methods for the measurement of the velocity fluctuation of flows. It consists of the particle mask correlation (PMC) method and the KC method. The correlation coefficient calculation has the largest computational overhead in the PMC method. In this paper, a hardware of the correlation coefficient calculation is designed and accelerated by the zigzag tracing, the modification of the correlation coefficient equation, and parallel processing. The processing speed and circuit size of the design are evaluated.