LiDAR-Iris

*LiDAR-Iris for Loop-Closure Detection*

— In this work, a global descriptor for a LiDAR point cloud, called LiDAR Iris, is proposed for fast and accurate loop-closure detection. A binary signature image can be obtained for each point cloud after a couple of LoGGabor filtering and thresholding operations on the LiDAR-Iris image representation. Given two point clouds, the similarity of them can be calculated as the hamming-distance of two corresponding binary signature images extracted from the two point clouds, respectively. Our LiDAR-Iris method can achieve a pose-invariant loop-closure detection with the Fourier transform of the LiDAR-Iris representation if assuming a 3D (x,y,yaw) pose space, although our method can generally be applied to a 6D pose space by re-aligning point cloud with an additional IMU sensor. Experimental results on five road-scene sequences demonstrate its excellent performance in loop-closure detection. Cheers!

Reference paper: 

Ying Wang, Zezhou Sun, Cheng-Zhong Xu, Sanjay Sarma, Jian Yang, and Hui Kong, LiDAR-Iris for Loop Closure Detection, IEEE International Conference on Intelligent Robotics and Systems (IROS) 2020 (oral presentation)