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Related Experiment Video

Updated: Nov 18, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

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Marker-Based Method for Recognition of Camera Position for Mobile Robots.

Dong-Gi Gwak1,2, Kyon-Mo Yang1, Min-Ro Park1

  • 1HRI Research Center, Korea Institute of Robotics & Technology Convergence, Pohang 37553, Korea.

Sensors (Basel, Switzerland)
|February 9, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a robust strategy for mobile robot position recognition using markers. It enhances camera perception in dynamic environments with novel marker designs and automatic position updates.

Keywords:
artificial markerindoor localizationmobile robotposition recognition

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Area of Science:

  • Robotics
  • Computer Vision

Background:

  • Accurate position recognition is crucial for mobile robot navigation in complex and changing environments.
  • Existing methods often require frequent updates to internal robot parameters when marker information changes.

Purpose of the Study:

  • To propose a flexible and adaptable strategy for estimating camera position on mobile robots.
  • To enhance marker recognition capabilities for mobile robots operating in real-world conditions.

Main Methods:

  • Directly acquiring marker information (ID, size, type) for relative camera positioning.
  • Introducing novel nested and hierarchical markers to improve recognition during robot movement.
  • Implementing automatic marker position updates based on a reference marker for dynamic environments.

Main Results:

  • The proposed marker system allows for flexible updates of identification information without altering robot system parameters.
  • Nested markers improve recognition for vertical take-off and landing robots (e.g., drones).
  • Hierarchical markers enhance recognition for horizontally moving robots (e.g., wheeled robots).
  • The method automatically recalculates marker positions when the robot's operational area changes.

Conclusions:

  • The developed strategy offers a versatile solution for mobile robot position estimation.
  • Novel marker designs and adaptive updating mechanisms improve robustness in real-world robotic applications.
  • Experimental validation confirms the effectiveness of the proposed position recognition methods.