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Active Pose Relocalization for Intelligent Substation Inspection Robot

Jiang Qian, Yadong Liu, Yingjie Yan, Peng Xu, Ling Pei, Xiuchen Jiang

发表年份
2022
引用次数
25

摘要

Intelligent inspection robots widely applied in substations are required to capture the inspection image consistent with the calibration image during routine inspection of electrical equipment. However, it is a challenging work for the inspection robot to capture the inspection image meeting the requirement due to navigation error and mechanical wear. To address this problem, an active pose relocalization (APR) method is proposed in this article. Specifically, an error model describing the relationship between the pixel error in the image plane and the robot pose error is established. Then, a decoupling three-stage proportional–integral control strategy based on the error model is provided to relocate the robot to the calibration pose, wherein, a translation error estimation algorithm based on homography transformation is proposed to compute the absolute translation scale between calibration and inspection poses, which avoid the degradation problem of the classic 2-D–2-D pose estimation algorithm. Finally, the performance of the proposed APR method is demonstrated through comparative relocalization experiments of ten calibration points in virtual and real-world environments, respectively.

关键词

Computer visionArtificial intelligenceRobotPoseComputer scienceCalibrationHomographyPixel3D pose estimationTranslation (biology)

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