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An immune-inspired swarm aggregation algorithm for self-healing swarm robotic systems.

J Timmis¹, A R Ismail², J D Bjerknes³

¹Department of Electronics, University of York, Heslington, York YO10 5DD, UK.

|May 15, 2016

Summary

This study introduces self-healing swarm robotics inspired by the immune system to address robot failures. The novel approach enhances swarm resilience and team performance, particularly against partial failures.

Keywords:

Artificial immune systems Self-repair Swarm robotics

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Area of Science:

Robotics
Artificial Intelligence
Bio-inspired Systems

Background:

Swarm robotics relies on decentralized coordination with limited communication.
While fault tolerance is a key benefit, swarms are vulnerable to specific failures.
Partially failed robots significantly degrade swarm performance.

Purpose of the Study:

To propose a self-healing mechanism for swarm robotic systems.
To mitigate the detrimental effects of robot failures on swarm behavior.
To draw inspiration from biological immune systems for robotic repair.

Main Methods:

Developed an immune-inspired approach for self-healing in swarms.
Utilized granuloma formation as a model for containment and repair.
Applied the approach to a swarm performing team work tasks.

Main Results:

The proposed method enables recovery from certain failure modes during swarm operation.
Successfully addressed issues caused by partially failed robots.
Improved overall swarm behavior and resilience.

Conclusions:

Immune-inspired self-healing is effective for swarm robotics.
This approach enhances robustness against critical failure types.
The study demonstrates a viable path towards more reliable swarm systems.