Obstacle detection based on the hybrid road plane under the weak calibration conditions

This paper presents a new obstacle detection method that is achieved on the depth image. This obstacle detection method can be used both in clumsy office environments and in natural environments. In this paper we focus our attention on the obstacle detection in the case of pitch angle variation (weak calibration conditions) due to uneven-road surface. The proposed obstacle detection has, mainly, two characteristics. One is the time efficiency aspect in the labelling of detected obstacles, which is achieved on the binarized depth image. The contour pixels of the obstacles of the binarized depth image have 3D information. The other is flexibility aspect in road plane that is generated by the LDPD (local difference probability distance) road classification. The shape of the road plane reflects the natural road surface by implementing hybrid road plane that consists of rough road plane and dedicated road plane. The real-time implementation is possible due to the time efficient grouping and labelling. Even obstacle detection is achieved on the depth image. The error of obstacle detection due to the change in height and position of the road plane by pitch angle variation is corrected by the proposed hybrid road plane.