A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots.

Area of Science:

• Robotics
• Sensor Systems
• Control Systems

Background:

• Spherical robots offer efficient locomotion and hazardous environment tolerance, ideal for surveillance and exploration.
• Existing spherical robots often lack robust obstacle avoidance, relying on 'hit and run' tactics.
• Miniature spherical robots with sensitive sensors require advanced, non-intrusive obstacle avoidance solutions.

Purpose of the Study:

• To develop a compact and power-efficient obstacle detection and avoidance system for miniature spherical robots.
• To enable intelligent avoidance behavior by detecting obstacle presence and approach direction.
• To enhance the safety and operational reliability of spherical robots in complex environments.

Main Methods:

• A passive magnetic field-based system was designed for compact and power-efficient operation.
• The system detects ferromagnetic obstacles and their approaching direction.
• Trajectory tracking methods were adapted using detection information for intelligent avoidance strategies.

Main Results:

• The developed system successfully detects ferromagnetic obstacles and their approach direction.
• Optimized design enhanced obstacle detection performance.
• Experimental validation confirmed the effectiveness of the avoidance strategies.

Conclusions:

• The proposed magnetic field-based system provides an effective solution for obstacle avoidance in miniature spherical robots.
• This technology enhances robot safety and autonomy, expanding their application scope.
• The system's compact and power-efficient nature makes it suitable for sensitive, small-scale robotic platforms.