3-D Dense Rangefinder Sensor With a Low-Cost Scanning Mechanism

Abstract

LiDAR sensors have been widely applied in autonomous robotics and autonomous systems. High-channel LiDARs or multiple low-channel LiDARs are adopted in these applications to overcome the poor vertical resolution of point clouds, as this scenario can lead to high costs. Here, as a means to improve the vertical resolution of point clouds and lower the cost, we present a 3-D dense rangefinder sensor composed of a low-channel LiDAR, a camera, a brush-less motor, and a crank-link system to replace the traditional LiDAR. A special registration method is designed to register the high-dynamic point cloud. The measurement uncertainty of this method is analyzed. In addition, a 3-D object detection method is used to obtain the 3-D pose of obstacles by combining the dense point cloud and an image-based 2-D object detection algorithm. Finally, several experiments are performed to evaluate the effectiveness of the proposed 3-D rangefinder sensor.