Multi-Objective Optimisation of Robotic Active Particle Swarms for Continuous Repair of Large Scale High Value Structures

The manufacture and creation of large scale high value structures has been done by humans for centuries. Examples include the Egyptian pyramids, Bridges, Modern Skyscrapers to mention a few. These structures are large but also provide a high value in terms of economy, culture, display of prestige to mention a few. With advances in space technology, we are bound to see these large scale high value structures constructed in space. The vacuum of space present us with the challenges of repairing these structures. This is due to the inhospitable and dangerous environment of space. With increasing number of structures in space, there is bound to be more debris created resulting in high impact damages to these high value structures. Inspired by the biological blood clotting process and biological active particles, in this work, we propose the use of a swarm of live on artificial active particles for the purposes of continuous and timely repair of these structures. We tackle one of the challenges of artificial active particles research; the ability to navigate in crowded and obstacle filled environments. This challenge can be viewed from the perspective of a constrained multi-objective optimisation problem in which a balance between exploration of an environment and its exploitation needs to be achieved while taking into consideration the various other constraints that apply to an active particle. In this work, we show how artificial active particles could avoid obstacles in their environment through the use of an exploration mechanism and find damaged sites. Our results show that as the ability to explore increases, the active particles are able to navigate around obstacles and find a damaged site. However, there is a limit to this.