We have developed a new type of 3D LIDAR, which is small, light weight and low cost. The size and weight are important factors of the aimed sensor to use with wide range of robot vehicles, helicopters and airplane, and small vehicles. To achieve compact size and light weight construction the sensor has single pair of laser transmitter and receiver, and scanning motor on which a vibrating mirror is placed. The mirror is driven by the resonant frequency current supplied through contactless power supply unit. Experimental results of the prototype shows that the sensor of comparable size and weight with recent 2D sensors can obtain 3D range data of 8000 points in 20 Hz with 270 degree horizontal and 40 degree vertical views both in indoor and outdoor.

Our long term goal is to integrate the position-based navigation with visual road following in order to build a more robust and reliable road navigation system. In this paper, we describe the first part of the project: constructing a navigation system that can build maps of highways and landmarks, and use those feature for position-based navigation. Speed and yaw rate gyro sensors are used for vehicle motion detection, and a millimeter wave radar system is used for landmark detection. To achieve position estimation and error correction, we use an extended Kalman filter. First, a map is built without previous knowledge of landmarks while human drives the vehicle. Then, at the stage of autonomous navigation, the previously produced map is used for position estimation. The experimental results show that a map produced by the proposed method can be used for later navigation, and that vehicle position is estimated accurately.