Local Bearing Estimation for a Swarm of Low-Cost Miniature Robots

Area of Science:

• Robotics
• Artificial Intelligence
• Computer Science

Background:

• Swarm robotics relies on decentralized control of numerous simple robots.
• Effective swarm communication requires accurate range and bearing information between individuals.
• Existing solutions may be costly or not suitable for miniature robots.

Purpose of the Study:

• To develop an open-source, low-cost communication module for miniature swarm robots.
• To create a precise mathematical model for estimating the bearing of neighboring robots.
• To optimize the communication module's hardware and software for enhanced performance.

Main Methods:

• Development of a novel, low-cost communication module for miniature robots.
• Mathematical modeling of neighbor bearing estimation using systematic experiments.
• Optimization of model parameters via a genetic algorithm.
• Hardware layout optimization involving sensor arrangement and angular displacement.

Main Results:

• A functional, open-source, low-cost communication module was successfully developed.
• A precise mathematical model for bearing estimation was established and optimized.
• Hardware re-arrangement led to significant improvements in bearing estimation accuracy.
• Combined software and hardware optimization enhanced overall system precision.

Conclusions:

• The developed communication module offers a reliable and cost-effective solution for swarm robotics.
• Optimized bearing estimation is crucial for effective decentralized control in robot swarms.
• Integrated hardware and software optimization strategies can substantially improve robotic system performance.