Domain Knowledge-based Automatic Parameter Selection for 2D/3D Line Segment Detection in Semi-unstructured Environment

One of the fundamental problems in mobile robot navigation in challenging environment is to improve autonomy in the sensor information processes. This paper presents an automatic parameter selection method for path recognition of outdoor semi-unstructured environment, based on human knowledge on the paths. As a preliminary process for path recognition, line segment detection integrating 2D image and 3D point cloud is adopted. Human knowledge on the path, line segments are mostly horizontal and around the ground level, is reflected to parameter selection through Pareto optimality in the multiple objective optimization. The proposed selection was evaluated by depth images taken in outdoor environments where boundaries of paths are obscure. It was shown in the experiment that resolution and edge parameters are influential to boundary detection performance. It was verified that the proposed method could select appropriate set of processing parameters based on the knowledge. The proposed idea is expected to contribute automatic selection of sensor modalities for more various environmental recognition scenarios.