GeoLCR: Attention-based Geometric Loop Closure and Registration

2023/02/27 by Liang, Jing, Son, Sanghyun, Lin, Ming +1
#FOS: Computer and information sciences #Robotics (cs.RO)

paper · doi:10.48550/arxiv.2302.13509

Abstract

We present a novel algorithm specially designed for loop detection and registration that utilizes Lidar-based perception. Our approach to loop detection involves voxelizing point clouds, followed by an overlap calculation to confirm whether a vehicle has completed a loop. We further enhance the current pose's accuracy via an innovative point-level registration model. The efficacy of our algorithm has been assessed across a range of well-known datasets, including KITTI, KITTI-360, Nuscenes, Complex Urban, NCLT, and MulRan. In comparative terms, our method exhibits up to a twofold increase in the precision of both translation and rotation estimations. Particularly noteworthy is our method's performance on challenging sequences where it outperforms others, being the first to achieve a perfect 100% success rate in loop detection.

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