Abstract
The author has been developing a safe driving system of mobile objects such as silver cars, mobility scooters and so on by using depth sensors which can capture range data of VGA size. If the geometrical relation between the sensor and the space is completely known, each point of the captured range data can be classified into three groups: upper than the ground, on the ground, and lower than the ground. However, it is essential to be able to deal with the unpredictable change of the posture of the sensor due to the movement of the mobile vehicle. The author developed an online estimation scheme of the posture including pitch angle, roll angle, and height from the observed data in the framework of optimization. In this paper, the author proposes an estimation scheme based on the state space model and apply Extended Kalman Filter for the same application problem. By comparing them, we will compare the algorithms by experimental results.
