Back to the program.
Self-Organized Flocking with a Mobile Robot Swarm
Ali Emre Turgut
Kovan Research Lab.
Middle East Techical University
Computer Engineering Dept.


In this presentation, we discuss self-organized flocking using a swarm of mobile robots. We first present a mobile robot platform having two novel sensing systems developed specifically for swarm robotic studies. We describe its infrared-based short-range sensing system, capable of measuring the range to obstacles and detecting kin robots. In particular, we describe a novel sensing system called the virtual heading sensor (VHS), which combines a digital compass and a wireless communication module to form a scalable method for sensing the relative headings of neighboring robots. We propose a behavior based on heading alignment and proximal control and show that it is capable of generating self-organized flocking in a group of seven robots. Then, we propose a number of metrics to evaluate the quality of flocking and use them to evaluate four main variants of this behavior. We characterize and model the sensing abilities of the robots and develop a physics-based simulator that is verified against the physical robots for flocking in open environments. After showing in simulation that we can achieve flocking in a group of up to 1000 robots in an open environment, we perform experiments to determine the performance of flocking under different controller parameters and characteristics of VHS using the predefined metrics. In the experiments, we vary the three main characteristics of VHS, namely: (1) The amount and nature of noise in heading measurement,(2) The number of neighboring robots that can be "heard", and (3) the range of wireless communication. Our results show that range of communication is the main factor that determines the scale of flocking, and that the behavior is highly robust against the other two characteristics. We extend an existing particle-based model to determine the phase transition characteristics of of flocking under different VHS characteristics. An analytical treatment of the model is also presented and verified against the results obtained from experiments in a physics-based simulator. The presentation ends up with the discussion on our recent studies including control of mobile robot swarms via informed individuals and the effects of flocking in long-range travels using a swarm of physical and simulated mobile robots.


Swarm robotics, Flocking, Self-organization, Control of robot swarms, Migration