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Title: Bio-inspired self-organizing swarm robotics
Author: Ramezan Shirazi, Ataollah
ISNI:       0000 0004 6494 8554
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 2017
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Swarm robotics is the collaboration of a large number of robots to accomplish a set of specified tasks. It has great potential for the generation of self-organizing adaptive systems, where simple behaviours at agent level result in complex behaviours at swarm level. These systems promise to be robust, flexible, and scalable, and have many innovative applications in the future. Elimination of a central controller and instead relying on local awareness and distributed decision making are the main distinguishing characteristics of such, systems which make them different from classical engineering and necessitate a different design methodology. The challenges to design a control mechanism for self-organizing swarm robotic systems mainly come from the difficulty of mapping between the macroscopic behaviours of a swarm and the microscopic behaviours of its individual agents, and also decision making based on local awareness. Nature presents the best examples of self-organising collective systems. They can be divided into two categories, animal collective behaviours, and cellular organs. Although studying animal collective behaviours paves the way for understanding the principles of self-organizing collective systems, cellular organs show more complex behaviours and structures. The goal of this research is to adapt cellular morphogenesis mechanisms for collective behaviours in a swarm of minimalist robots. The trade of between the size of a swarm and the complexity of involved robots necessitates using simpler and cheaper robots. In addition, miniaturization of robots for future micro-robotic applications require to minimize the number of on-board devices in robots. In this thesis, we focus on developing minimalist algorithms inspired by biological morphogenesis for collective swarm behaviours, including collective flocking, target following, and target enclosure. The proposed algorithms are applicable to highly restricted robots without global positioning, directional sensing, motion feedback, and long-range communication devices. At first, I show how morphogens can retain the integrity and original shape of a swarm of robots without directional sensing, while the swarm moves and interacts with the environment. Then, a coordinated motion strategy is presented in order to preserve connectivity of a real swarm of minimalist robots following a target in their environment. Finally, a new approach is presented for target enclosure with a control over the shape of aggregation around the target. In this approach, a morphogen gradient produced by a target reacts with a second one diffusing through the edge of aggregation in order to spot weak points of the aggregation. The last two algorithms implemented in a real swarm of Kilobots.
Supervisor: Jin, Yaochu Sponsor: Seventh Framework Programme, European Union ; Department of Computer Science, University of Surrey
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available