PoseRL-Net: human pose analysis for motion training guided by robot vision

PoseRL-Net not only improves pose estimation accuracy but also provides crucial support for intelligent decision-making and motion planning in robots operating in dynamic and complex scenarios, offering significant practical value for collaborative robotics.

Authors

Bin Liu (ORCID: https://orcid.org/0000-0002-3977-8800)
Hui Wang (ORCID: https://orcid.org/0000-0001-9245-674X)

Institutions

Shanghai Jian Qiao University (CN)

Publication Details

Journal: Frontiers in Neurorobotics
Published: 2025-03-05
DOI: https://doi.org/10.3389/fnbot.2025.1531894
Citations: 2
Primary Topic: Human Pose and Action Recognition
Type: article
Field-Weighted Citation Impact: 2.55

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article

PoseRL-Net: human pose analysis for motion training guided by robot vision

Bin Liu, Hui Wang

Mar 5, 2025

2 citations

Frontiers in Neurorobotics

Human Pose and Action Recognition

2.55

article

PoseRL-Net: human pose analysis for motion training guided by robot vision

Bin Liu, Hui Wang

March 5, 2025article en

2 citations

Abstract

Frontiers in NeuroroboticsVol. 19

Shanghai Jian Qiao University (CN)

Peace, Justice and strong institutions

Openalex Percentile: Top 12%

Human Pose and Action Recognition

2.55

DOI Open Access PDF OpenAlex

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PoseRL-Net: human pose analysis for motion training guided by robot vision — Bin Liu, Hui Wang · Frontiers in Neurorobotics (2025) | TGRS Research Map | TGRS