A 675.2 nJ/frame Keypoint Extraction Processor for LiDAR-based SLAM

An energy-efficient keypoint extraction processor is proposed for real-time LiDAR-based SLAM. The keypoints are extracted from sorted curvature map, that sorting process is the main bottleneck occupying 85.9% of KE latency. The extracted keypoints occupy 7.9% of total input points, that sorting process is operated with huge redundant data. To address this, near-keypoint removal and candidate filtering unit are proposed to exclude 92.1% of redundant data which is not extracted as keypoints removing 42.8-63.0% of data, resulting in 19.5-43.0% of latency reduction. Additionally, input points vary 31.9× in channel-wise and 5.1× in frame-wise, causing huge workload variance. Reconfigurable radix sorting is proposed, that 16 radix-based sorting with 0.34 MB/frame low-memory bandwidth is operated with low workload. With a high workload, 2 radix-based sorting can achieve 28.1 μs of low processing time operating with high speed. The proposed processor is fabricated in 28 nm CMOS technology, occupying 0.57 mm², with 7.26 mW power consumption and 675.2 nJ/frame of efficiency which is 998661× higher than the previous CPU.