Swarm robotics: a tool to study collective behaviours in biological systems
Dr. Eliseo Ferrante
Middlesex University Dubai
Swarm robotics studies the design of collective behaviours for swarms of robots, that is, it tries to understand how individual robots should behave and interact with each other in such a way as to achieve a collective-level, emergent behaviour. Swarm robotics has both a scientific as well as an engineering soul. From a scientific perspective, it aims at using robots as a model of real living organisms that live in groups, such as ants, bees, birds, fish, in order to understand key behavioural properties that lead to their self-organisation, and how and why such behaviours evolved. From an engineering perspective, the goal is to use this understanding to design robots with minimal hardware and communication requirements, in order to use their emergent self-organising collective behaviour to solve problems in large unstructured and unpredictable environments. In this talk, after giving a short overview on the research projects I worked on, I will specifically focus on one that has been carried out at the interface between robotics and evolutionary biology. I will present a study on the evolution of task specialisation and task partitioning in robot and ants societies. In this study, using computer simulations, we evolved for the first time the task allocation mechanism as well as the individual behaviour needed to carry out the individual sub-tasks in a foraging scenario inspired by leaf-cutter ants. I will show the implications of my studies on both engineering and biology.
Dr. Eliseo Ferrante holds a senior lecturer position at Middlesex University Dubai. He was awarded a Ph.D. in Applied Sciences from the Université Libre de Bruxelles (ULB) in 2013. Dr. Ferrante has authored more than 30 peer-reviewed publications, among which 15 publications in international peer review journals, and 18 articles between peer-reviewed conference, workshops, and video proceedings. Some of Dr. Ferrante’s journal articles have been published in prestigious journals with high impact factors, including Physical Review Letters (IF 2014: 7.51) and Plos Computational Biology (IF 2014: 4.62). He also authored a survey article which has garnered 250+ citations since 2013. His Google Scholar H-index is 13, and the total number of citations is over 900. Dr. Ferrante’s research was featured in international and national magazines, including Science Magazine, IEEE Spectrum, Sciences et Avenir (France), the Italian National News Agency (ANSA), and La Repubblica (Italy). According to the Altmetric website, Dr. Ferrante’s Plos Computational Biology article is ranked among the top 40 most impactful articles published in the same journal and in the 99th percentile of all articles ever tracked by the website. Dr. Ferrante’s research focuses on swarm robotics studies from an interdisciplinary perspective comprising computational, statistical physics, and evolutionary models of collective behaviors. Some of the phenomena he studies include collective motion, task specialization, and collective decision-making in animals, artificial agents and robots. His methodological expertise includes computer simulations, real robot experiments, evolutionary and mathematical models.
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