Robotic Swarming Without Inter-Agent Communication

Many physical and algorithmic swarms utilize inter-agent communication to achieve advanced swarming behaviors. These swarms are inspired by biological swarms that can be seen throughout nature and include bee swarms, ant colonies, fish schools, and bird flocks. These biological swarms do not utilize inter-agent communication like their physical and algorithmic counterparts. Instead, organisms in nature rely on a local awareness of other swarm members that facilitates proper swarm motion and behavior. This research aims to pursue an effective swarm algorithm using only line-of-sight proximity information and no inter-agent communication. It is expected that the swarm performance will be lower than that of a swarm utilizing inter-agent communication. Various sensors were studied and considered for this project but infrared sensors were ultimately selected. These sensors were then modeled in software using a neural network in order to calculate the minimum number of infrared transmitters and receivers necessary for each agent while still ensuring the proper functionality of the swarm. A physical swarm was designed and constructed using the selected number and type of infrared sensors, DC stepper motors, a 16-bit microprocessor, and additional infrared proximity sensors. The performance of the physical robots was compared to the performance of the simulated robots under similar conditions. It was observed that the physical and simulated swarms performed similarly and that swarm behavior with no inter-agent communication was successfully achieved