ArticleSensors (Basel, Switzerland)2021
Digital Twin-Driven Human Robot Collaboration Using a Digital Human.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 88 citations in OpenAlex.
- Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies.Sensors (Basel, Switzerland) · 2023Pooled it
- A scoping review of human digital twins in healthcare applications and usage patterns.NPJ digital medicine · 2025Article
- A Quantifiable Comprehensive Evaluation Method Combining Optical Motion Capture and Simulation-Assessing the Layout Design of Special Vehicle Cabins.Sensors (Basel, Switzerland) · 2025Article
- Construction Method of a Digital-Twin Simulation System for SCARA Robots Based on Modular Communication.Sensors (Basel, Switzerland) · 2024Article
- Scalability of Cyber-Physical Systems with Real and Virtual Robots in ROS 2.Sensors (Basel, Switzerland) · 2023Article
- The Development of a Digital Twin Framework for an Industrial Robotic Drilling Process.Sensors (Basel, Switzerland) · 2022Article
- Digital Twin for Human-Robot Interactions by Means of Industry 4.0 Enabling Technologies.Sensors (Basel, Switzerland) · 2022Article
- Beyond Digital Twins: Phygital Twins for Neuroergonomics in Human-Robot Interaction.Frontiers in neurorobotics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances are being made in applying digital twin (DT) and human-robot collaboration (HRC) to industrial fields for safe, effective, and flexible manufacturing. Using a DT for human modeling and simulation enables ergonomic assessment during working. In this study, a DT-driven HRC system was developed that measures the motions of a worker and simulates the working progress and physical load based on digital human (DH) technology. The proposed system contains virtual robot, DH, and production management modules that are integrated seamlessly via wireless communication. The virtual robot module contains the robot operating system and enables real-time control of the robot based on simulations in a virtual environment. The DH module measures and simulates the worker's motion, behavior, and physical load. The production management module performs dynamic scheduling based on the predicted working progress under ergonomic constraints. The proposed system was applied to a parts-picking scenario, and its effectiveness was evaluated in terms of work monitoring, progress prediction, dynamic scheduling, and ergonomic assessment. This study demonstrates a proof-of-concept for introducing DH technology into DT-driven HRC for human-centered production systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.