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Updated: Jul 24, 2025

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The Energy Efficiency Multi-Robot System and Disinfection Service Robot Development in Large-Scale Complex

Chin-Sheng Chen1, Feng-Chieh Lin1, Chia-Jen Lin1,2

  • 1Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei 10608, Taiwan.

Sensors (Basel, Switzerland)
|July 8, 2023
PubMed
Summary
This summary is machine-generated.

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This study introduces an energy-saving multi-robot system that reduces computing energy consumption by 54% during long-term operations. The system maintains high localization accuracy, crucial for service robots in complex environments.

Area of Science:

  • Robotics and Control Systems
  • Artificial Intelligence
  • Computer Vision

Background:

  • Service robots with graphical computing are increasingly used, but long-term Visual Simultaneous Localization and Mapping (VSLAM) reduces energy efficiency.
  • Localization failures persist in large-scale environments with dynamic crowds and obstacles, impacting robot reliability.
  • Existing multi-robot systems face challenges in energy management and robust localization for extended operations.

Purpose of the Study:

  • To propose an innovative energy-saving multi-robot control system, EnergyWise, to address the limitations of current VSLAM implementations.
  • To enhance robot energy efficiency and localization accuracy in complex, large-scale environments through intelligent VSLAM activation.
  • To validate the system's performance in a real-world disinfection task during the COVID-19 pandemic.
Keywords:
EKFMRSVSLAMenergy savingmulti-robot systemservice robot

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Main Methods:

  • Developed the EnergyWise multi-robot system based on ROS, incorporating an energy-saving selector algorithm to control VSLAM activation.
  • Implemented a novel 2-level Extended Kalman Filter (EKF) method and integrated Ultra-Wideband (UWB) global localization for robust pose estimation.
  • Deployed three disinfection service robots for a 10-day operation in a large, complex experimental site.

Main Results:

  • Achieved a significant 54% reduction in computing energy consumption during long-term robot operations.
  • Maintained a high localization accuracy of 3 cm, demonstrating the system's effectiveness in complex environments.
  • Successfully demonstrated the system's capability in a practical disinfection application.

Conclusions:

  • The proposed EnergyWise system offers a viable solution for improving energy efficiency in multi-robot systems.
  • The intelligent VSLAM activation and robust localization mechanisms are critical for reliable long-term robot operation.
  • This approach is well-suited for service robots operating in dynamic and large-scale environments.