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August 13, 2026Journal of Field RoboticsOpen Access

Multi‐Modal Perception in Dynamic Occlusion Scenarios: A Human Pose Estimation Approach in Human‐Robot Collaboration

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Authors

LZLijie ZhouHWHongyu WangXLXingqi Li

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Overview

Randomized trial shows improved pose estimation and collision detection in human-robot collaboration, indicating enhanced safety measures.

Key Points

  • The aim is to develop a robust human pose estimation method for dynamic occlusion scenarios in human-robot collaboration.
  • Proposed a skeletal pose and minimum-distance fusion (SPMF) approach.
  • Utilized OpenPose-based skeletal model for 3D joint coordinate estimation.
  • Applied Gilbert-Johnson-Keerthi (GJK) algorithm for calculating minimum human-robot distance.
  • The SPMF method outperformed existing fusion methods under severe occlusion.
  • Achieved real-time collision detection during human-robot collaboration.
  • Demonstrated accurate pose recognition for industrial safety applications.

Cite This Study

Zhou et al. (2026) studied this question.

synapsesocial.com/papers/6a7d75ad2b0e0cff3f63e6fchttps://doi.org/10.1002/rob.70312
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