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English(EN) CalibSwitch: Observation-Driven Camera-LiDAR Extrinsic Recovery and Selective Maintenance for Multimodal Perception

CalibSwitch框架增强了用于多模态感知的相机-激光雷达传感器校准

研究人员开发了CalibSwitch,一个旨在提高多模态感知系统中相机-激光雷达传感器校准的准确性和可靠性的新框架。该系统将过程分为绝对外参恢复和选择性状态维护,利用跨模态绝对外参生成器(CAEG)和选择性循环校准策略(SRCP)。CalibSwitch在nuScenes数据集上表现强劲,实现了较低的平均平移和旋转误差,并且与传统的门控方法相比,在多模态检测器性能方面显示出显著的改进。 AI

影响 这项研究通过提高传感器融合的可靠性,可能为自动驾驶汽车和机器人领域带来更强大、更准确的感知系统。

排序理由 该集群描述了一篇在arXiv上发表的研究论文,详细介绍了一个新的传感器校准框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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CalibSwitch框架增强了用于多模态感知的相机-激光雷达传感器校准

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该集群描述了一篇在arXiv上发表的研究论文,详细介绍了一个新的传感器校准框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Haifa Zhang, Yijing Wang, Zhiqiang Zuo ·

    CalibSwitch:面向多模态感知的观测驱动式相机-激光雷达外参恢复与选择性维护

    arXiv:2610.41352v1 Announce Type: cross Abstract: Camera--LiDAR perception on mobile robots and intelligent vehicles depends on reliable sensor geometry throughout deployment. Installation variations create uncertainty in the initial extrinsics, while changing observation quality…