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

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.