SAGE-ICP: Semantic Information-Assisted ICP

• URL: http://arxiv.org/abs/2310.07237v1
• Date: Wed, 11 Oct 2023 06:58:22 GMT
• Title: SAGE-ICP: Semantic Information-Assisted ICP
• Authors: Jiaming Cui, Jiming Chen, Liang Li
• Abstract summary: This paper proposes a novel semantic information-assisted ICP method named SAGE-ICP. The semantic information for the whole scan is timely and efficiently extracted by a 3D convolution network. Unlike previous semantic-aided approaches, the proposed method can improve localization accuracy in large-scale scenes.
• Score: 14.280779681381016
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Robust and accurate pose estimation in unknown environments is an essential part of robotic applications. We focus on LiDAR-based point-to-point ICP combined with effective semantic information. This paper proposes a novel semantic information-assisted ICP method named SAGE-ICP, which leverages semantics in odometry. The semantic information for the whole scan is timely and efficiently extracted by a 3D convolution network, and these point-wise labels are deeply involved in every part of the registration, including semantic voxel downsampling, data association, adaptive local map, and dynamic vehicle removal. Unlike previous semantic-aided approaches, the proposed method can improve localization accuracy in large-scale scenes even if the semantic information has certain errors. Experimental evaluations on KITTI and KITTI-360 show that our method outperforms the baseline methods, and improves accuracy while maintaining real-time performance, i.e., runs faster than the sensor frame rate.

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