Hanwen Wang

North Carolina State University

Works (6)

Updated: April 22nd, 2024 07:44

2023 article

An Image-Based Human-Robot Collision Avoidance Scheme: A Proof of Concept

Xie, Z., Lu, L., Wang, H., Li, L., & Xu, X. (2023, June 8). IISE TRANSACTIONS ON OCCUPATIONAL ERGONOMICS & HUMAN FACTORS, Vol. 6.

By: Z. Xie n, L. Lu n, H. Wang n , L. Li  n & X. Xu n 

author keywords: Collaborative robot; collision avoidance; computer vision; robot kinematics; risk assessment
TL;DR: A reliable system for human-robot collision avoidance system employing computer vision that enables proactive prevention of dangerous collisions between humans and robots and greatly extends the effective detection range compared to previous studies. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, NC State University Libraries
Added: July 31, 2023

2023 article

Improving Workers' Musculoskeletal Health During Human-Robot Collaboration Through Reinforcement Learning

Xie, Z., Lu, L., Wang, H., Su, B., Liu, Y., & Xu, X. (2023, May 22). HUMAN FACTORS, Vol. 5.

By: Z. Xie n, L. Lu n, H. Wang n , B. Su n, Y. Liu n & X. Xu n 

author keywords: robotics; computer-supported collaborations; human-automation interaction; job risk assessment; human-robot interaction
TL;DR: The proposed model-free reinforcement learning method can learn the optimal worker postures without the need for specific biomechanical models and can be applied to improve the occupational safety in robot-implemented factories. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, NC State University Libraries, ORCID
Added: May 23, 2023

2022 journal article

A mobile platform-based app to assist undergraduate learning of human kinematics in biomechanics courses

JOURNAL OF BIOMECHANICS, 142.

By: H. Wang n , Z. Xie n, L. Lu n, B. Su n, S. Jung n & X. Xu n 

author keywords: Joint angles; User interface; Computer vision; Undergraduate education; Self-relevant data
MeSH headings : Biomechanical Phenomena; Humans; Learning; Mathematics; Mobile Applications; Students
TL;DR: A mobile app that can serve as a potential instructional tool to assist in conducting human motion experiments in biomechanics courses and view various kinematics data for a selected joint or body segment in real-time through the user interface of the mobile device. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: September 6, 2022

2022 review

Mental stress and safety awareness during human-robot collaboration - Review

[Review of ]. APPLIED ERGONOMICS, 105.

By: L. Lu n, Z. Xie n, H. Wang n , L. Li  n & X. Xu n 

author keywords: Human-robot collaboration; Mental stress; Safety awareness; Workplace safety
Sources: Web Of Science, NC State University Libraries, ORCID
Added: June 28, 2022

2021 journal article

A computer-vision method to estimate joint angles and L5/S1 moments during lifting tasks through a single camera

JOURNAL OF BIOMECHANICS, 129.

By: H. Wang n , Z. Xie n, L. Lu n, L. Li  n & X. Xu n 

author keywords: Musculoskeletal disorders; Low-back injuries; Markerless motion tracking; Joint kinematics; L5/S1 joint moment
MeSH headings : Biomechanical Phenomena; Computers; Humans; Lifting; Lumbar Vertebrae; Sacrum
TL;DR: This study showed computer vision could facilitate safety practitioners to quickly identify the jobs with high MSD risks through field survey videos using a single RGB camera and VideoPose3D, an open-source library with a fully convolutional model. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, NC State University Libraries
Added: November 29, 2021

2021 journal article

Lifting Posture Prediction With Generative Models for Improving Occupational Safety

IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 51(5), 494–503.

By: L. Li n, S. Prabhu n, Z. Xie n, H. Wang n , L. Lu n & X. Xu n 

author keywords: Generative models; lifting tasks; neural networks; occupational injuries; posture prediction
TL;DR: The results prove that using a generative model to predict lifting posture prediction is able to predict postures with reasonable accuracy and validity and can support biomechanical analysis and ergonomics assessment of a lifting task to reduce the risk of low back injuries. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, NC State University Libraries, ORCID
Added: September 27, 2021

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