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Lightweight Two-Layer Control Architecture for Human-Following Robot.

Gustavo A Acosta-Amaya1, Deimer A Miranda-Montoya2, Jovani A Jimenez-Builes2

  • 1Instrumentation and Control Department, Faculty of Engineering, Politécnico Colombiano Jaime Isaza Cadavid, Medellín 050022, Colombia.

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Summary

This study introduces a new control system for robots that helps them follow people indoors. The system uses a fuzzy logic controller and advanced algorithms, proving effective for assistive robotics.

Keywords:
RGB-D sensorautonomous robotbehavior-based control architecturecomputer visionembedded controllerfuzzy logic controlhuman-following robotmobile robotics

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Area of Science:

  • Robotics
  • Control Systems
  • Artificial Intelligence

Background:

  • Human detection and tracking are essential for safe human-robot interaction in indoor environments, especially for assistive robots.
  • The growing demand for assistance among the elderly and disabled fuels the development of advanced robotic systems.

Purpose of the Study:

  • To present a lightweight, two-layer control architecture for a human-following robot.
  • To integrate a fuzzy behavior-based control system with low-level embedded controllers for enhanced performance.

Main Methods:

  • Utilized an RGB-D sensor for capturing distance and angular data.
  • Implemented a fuzzy controller to generate motor speed set-points.
  • Developed low-level controllers using pole placement and internal model control (IMC) methods.

Main Results:

  • The robot successfully followed a person in real-time, maintaining a 1.3 m distance across five trials.
  • The internal model control (IMC) controller outperformed the pole placement controller in all evaluated metrics.
  • Experimental validation confirmed the architecture's effectiveness in real-world scenarios.

Conclusions:

  • The proposed control architecture provides a robust, real-time solution for human-following assistive robots with limited computational power.
  • The system's modularity and scalability support future advancements in personal assistance robotics.
  • This approach effectively addresses challenges in indoor human-robot interaction.