Target Pose Estimation Methods for Distribution Network Bypass Operation Robots

doi:10.3969/j.issn.1006-2475.2025.09.003

Abstract

Abstract:
Abstract： To replace humans in bypass operation tasks， robots need the ability to autonomously estimate the pose of target objects in complex work environments. Addressing the problem of real-time pose estimation of targets by bypass operation robots under complex backgrounds and varying lighting conditions， this proposes a 6D pose estimation algorithm （RTFT6D） based on improved YOLO-6D integrated with Transformer model. The YOLOv8 backbone network is modified to enhance inference speed， and a feature enhancement network incorporating the Transformer model is designed to improve the robustness of pose estimation. The experimental results show that the proposed algorithm surpasses most RGB image-based pose estimation algorithms in accuracy on the LINEMOD dataset， and it achieves excellent pose estimation performance for bypass operation targets under different lighting conditions.

Key words: Key words： distribution network bypass operation robot, pose estimation, YOLO-6D, YOLOv8, Transformer

CLC Number:

TP391.4

YAO Jie1, YIN Honghai1, WANG Dahai1, LI Runzi2, ZHANG Qianwen2, GUO Yu2. Target Pose Estimation Methods for Distribution Network Bypass Operation Robots[J]. Computer and Modernization, 2025, 0(09): 20-26.

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