LiDAR-Based Small-Sized Obstacle Detection for Mobile Robot

One of crucial issues for mobile robots navigation is dynamic obstacle avoidance, so the robot needs to detect these obstacles accurately and efficiently. In this paper, we propose a small-sized obstacle detection method with low cost, high efficiency and robustness based on the robot’s local observation (2-D LiDAR). For common small-sized obstacles including pedestrians and other robots of similar size, the proposed method is able to recognize them and estimate their velocity. Firstly, rising and falling edges are introduced into LiDAR-data, and by matching them all the possible small-sized obstacles are recognized. Then, the real-time velocity of small-sized obstacles is estimated using their historically recognized positions. Simulation experiments verify that our proposed method could acquire satisfactory detection accuracy under complex mutual occlusions.