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Related Experiment Video

Updated: Sep 11, 2025

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
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Low-Latency Edge-Enabled Digital Twin System for Multi-Robot Collision Avoidance and Remote Control.

Daniel Poul Mtowe1, Lika Long1, Dong Min Kim1,2

  • 1Department of ICT Convergence, Graduate School, Soonchunhyang University, Asan 31538, Republic of Korea.

Sensors (Basel, Switzerland)
|August 14, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an Edge-Enabled Digital Twin networked control system (E-DTNCS) for multi-robot collision avoidance. The new architecture significantly reduces latency and improves real-time control in dynamic environments.

Keywords:
collision avoidancedigital twinedge computinglow latencynetworked control system

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Edge Computing
  • Digital Twin Technology

Background:

  • Traditional multi-robot control systems face limitations due to network latency, bandwidth constraints, and lack of predictive capabilities.
  • Centralized cloud processing and direct sensor-to-controller communication hinder real-time performance in dynamic environments.

Purpose of the Study:

  • To propose a low-latency and scalable architecture for Edge-Enabled Digital Twin networked control systems (E-DTNCS).
  • To enhance multi-robot collision avoidance and remote control in latency-sensitive applications.

Main Methods:

  • Integration of edge computing for localized data preprocessing and feature extraction.
  • Utilization of Digital Twin (DT) technology for high-fidelity synchronization and predictive modeling.
  • Development of a real-world testbed with multiple mobile robots for empirical validation.

Main Results:

  • Significant reduction in collision rates observed with Digital Twin (DT) deployment.
  • Further improvements in responsiveness and collision avoidance achieved with E-DTNCS integration due to reduced latency.
  • Demonstrated effectiveness in handling real-time control tasks for multi-robot systems.

Conclusions:

  • The proposed E-DTNCS framework effectively combines edge intelligence and DT-driven control.
  • This approach advances the reliability, scalability, and real-time performance of multi-robot systems.
  • The framework holds potential for industrial automation and cyber-physical applications.