Road Curb Detection Using A Novel Tensor Voting Algorithm Road curb detection is very important and necessary for autonomous driving because it can improve the safety and robustness of robot navigation in the outdoor environment. In this paper, a novel road curb detection method based on tensor voting is presented. The proposed method processes the dense point cloud acquired using a 3D LiDAR. Firstly, we utilize a sparse tensor voting approach to extract the line and surface features. Then, we use an adaptive height threshold and a surface vector to extract the point clouds of the road curbs. Finally, we utilize the height threshold to segment different obstacles from the occupancy grid map. This also provides an effective way of generating highdefinition maps. The experimental results illustrate that our proposed algorithm can detect road curbs with near realtime performance.

Visual Road Boundary Detection based Local Path Planner We propose a realtime visual road detection based local path planner for autonomous navigation in unstructured environments. The system consists of two parts: road detection and local path planning. Road boundary model based on convolution neural network is trained for local road detection in image frame. After perspective transformation, the result is transformed to the vehiclexe2x80x99s frame for path planning. The road midline generated from the road boundaries is used to represent the reference local path. Priori information with the global navigation topology map is combined to solve multiroads selection. Finally, data fusion with historical detection results and predictive control of vehicle model is used for path optimization. In addition, obstacle avoidance combined with LIDAR perception is also taken into account to complete an autonomous navigation task in complex scenarios.A large number of experiments with various road conditions shows that the proposed method has a good adaptability and versatility for unstructured scenarios. The algorithm can effectively reduce the dependence on absolute positioning and LIDAR perception. So it is of great importance for autonomous navigation in scenarios without satellite or in unknown scenarios.