日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

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arXiv:2408.16867

CalTag: Robust calibration of mmWave Radar and LiDAR using backscatter tags

CalTag: Robust calibration of mmWave Radar and LiDAR using backscatter tags

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著者: Junyi Xu, Kshitiz Bansal, Dinesh Bharadia

分類: cs.RO, eess.SP

原文アブストラクト

The rise of automation in robotics necessitates the use of high-quality perception systems, often through the use of multiple sensors. A crucial aspect of a successfully deployed multi-sensor system is the calibration with a known object typically named fiducial. In this work, we propose a novel fiducial system for millimeter wave radars, termed as CalTag. CalTag addresses the limitations of traditional corner reflector-based calibration methods in extremely cluttered environments. CalTag leverages millimeter wave backscatter technology to achieve more reliable calibration than corner reflectors, enhancing the overall performance of multi-sensor perception systems. We compare the performance in several real-world environments and show the improvement achieved by using CalTag as the radar fiducial over a corner reflector.