- author = "Eliseo Ferrante",
- title = "Information Transfer in a Flocking Robot Swarm",
- school = "Universit\'e Libre de Bruxelles",
- year = "2013",
- address = "Belgium",
- keywords = "genetic algorithms, genetic programming, PSO, information transfer, collective motion, statistical physics, swarm robotics, real robots",
-
URL = "
http://bio.kuleuven.be/ento/ferrante/papers/FerrantePhD.pdf",
- size = "162 pages",
-
abstract = "In this dissertation, we propose and study methods for
information transfer within a swarm of mobile robots
that coordinately move, or flock, in a common
direction. We define information transfer as the
process whereby robots share directional information in
order to coordinate their heading direction. We
identify two paradigms of information transfer:
explicit information transfer and implicit information
transfer.
In explicit information transfer, directional information is transferred via communication. Explicit information transfer requires mobile robots equipped with a a communication device. We propose novel communication strategies for explicit information transfer, and we perform flocking experiments in different situations: with one or two desired directions of motion that can be static or change over time. We perform experiments in simulation and with real robots. Furthermore, we show that the same explicit information transfer strategies can also be applied to another collective behaviour: collective transport with obstacle avoidance.
In implicit information transfer, directional information is transferred without communication. We show that a simple motion control method is sufficient to guarantee cohesive and aligned motion without resorting to communication or elaborate sensing. We analyse the motion control method for its capability to achieve flocking with and without a desired direction of motion, both in simulation and using real robots. Furthermore, to better understand its underlying mechanism, we study this method using tools of statistical physics, showing that the process can be explained in terms of non-linear elasticity and energy-cascading dynamics.",
- notes = "Supervisor Marco Dorigo. in english",
