Visual servoing method of high voltage capacitor tower maintenance robot in bolt tightening

Yuze Wu, Jianbin Liao, Liangyu Liu, Yu Yan, Yunfei Ai, Yunxiang Li, Wang Wei
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Abstract

Purpose

This paper aims to address the challenges of the capacitor tower maintenance robot during bolt tightening in high-voltage substations, including difficulties in bolt positioning due to tilted angles and anti-bird cover occlusion and issues with fast and accurate docking of bolts while the base is moving.

Design/methodology/approach

This paper proposes a visual servoing method for the capacitor tower maintenance robot, including bolt pose estimation and visual servoing control. Bolt pose estimation includes four components: constructing a keypoint detection network to identify the approximate position, precise positioning, rapid prediction and calculation of bolt pose. In visual servoing, an improved position-based visual servoing (PBVS) is proposed, which eliminate steady-state error and enhance response speed during dynamic tracking by incorporating integral and differential components.

Findings

The bolt detection method exhibits high robustness against varying lighting conditions, partial occlusions, shooting distances and angles. The maximum positioning error at a distance of 250 mm is 2.8 mm. The convergence speed of the improved PBVS is 10% higher than that of the traditional PBVS when the base and target remain relatively stationary. When the base moves at a constant speed, the improved method eliminates steady-state error in dynamic tracking. When the base moves rapidly and intermittently, the maximum error of the improved method in the tracking process is 30% smaller than that of traditional PBVS.

Originality/value

This method enables real-time detection and positioning of bolts in an unstructured environment with tilt angles, variable lighting conditions and occlusion by anti-bird covers. An improved PBVS is proposed to enhance its capability in tracking dynamic targets.

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高压电容器塔维护机器人在拧紧螺栓时的视觉伺服方法
目的 本文旨在解决高压变电站电容器塔维护机器人在螺栓紧固过程中遇到的难题,包括倾斜角度和防鸟罩遮挡导致的螺栓定位困难,以及底座移动过程中螺栓快速准确对接的问题。螺栓姿态估计包括四个部分:构建关键点检测网络以识别近似位置、精确定位、快速预测和计算螺栓姿态。在视觉伺服方面,提出了一种改进的基于位置的视觉伺服(PBVS),通过整合积分和微分组件,消除了稳态误差,提高了动态跟踪时的响应速度。距离为 250 毫米时的最大定位误差为 2.8 毫米。当底座和目标相对静止时,改进型 PBVS 的收敛速度比传统 PBVS 高 10%。当基座匀速运动时,改进方法消除了动态跟踪中的稳态误差。当基地快速间歇移动时,改进方法在跟踪过程中的最大误差比传统 PBVS 小 30%。原创性/价值该方法可在倾斜角度、光照条件多变和防鸟遮挡的非结构化环境中实时检测和定位螺栓。提出了一种改进的 PBVS,以增强其跟踪动态目标的能力。
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