ATI-CTLO:基于时间间隔的自适应连续时间激光雷达测距仪

IF 4.6 2区 计算机科学 Q2 ROBOTICS IEEE Robotics and Automation Letters Pub Date : 2024-10-24 DOI:10.1109/LRA.2024.3486233
Bo Zhou;Jiajie Wu;Yan Pan;Chuanzhao Lu
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引用次数: 0

摘要

机器人的剧烈运动和环境地形特征造成的激光雷达扫描运动失真严重影响了三维激光雷达里程测量的定位和绘图性能。现有的失真校正解决方案很难在计算复杂性和准确性之间取得平衡。在这封信中,我们提出了一种基于时间间隔的自适应连续时间激光雷达测距法(ATI-CTLO),它基于简单高效的线性插值。我们的方法可以根据运动动态和环境退行性灵活调整控制节点之间的时间间隔。这种适应性提高了在各种运动状态下的性能,并改善了算法在退化环境,特别是特征稀少环境中的鲁棒性。我们在不同平台的多个数据集上验证了我们方法的有效性,其精确度与最先进的纯激光雷达里程测量方法相当。值得注意的是,在涉及剧烈运动和稀疏特征的情况下,我们的方法优于现有的纯激光雷达方法。
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ATI-CTLO: Adaptive Temporal Interval-Based Continuous-Time LiDAR-Only Odometry
The motion distortion in LiDAR scans caused by the robot's aggressive motion and environmental terrain features significantly impacts the positioning and mapping performance of 3D LiDAR odometry. Existing distortion correction solutions struggle to balance computational complexity and accuracy. In this letter, we propose an A daptive T emporal I nterval-based C ontinuous- T ime L iDAR-only O dometry (ATI-CTLO), which is based on straightforward and efficient linear interpolation. Our method can flexibly adjust the temporal intervals between control nodes according to the motion dynamics and environmental degeneracy. This adaptability enhances performance across various motion states and improves the algorithms robustness in degenerate, particularly feature-sparse, environments. We validated our method's effectiveness on multiple datasets across different platforms, achieving comparable accuracy to state-of-the-art LiDAR-only odometry methods. Notably, in situations involving aggressive motion and sparse features, our method outperforms existing LiDAR-only methods.
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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