Extension of the boid towards a bird-bot ontology for coordinating surveillance robotic devices

Abstract

This study extended the boid model to a bird-bot ontology for coordinating robotic devices deployed for surveillance purposes. The key attributes of the ontology are the boid rules, the environment, and meta-data on how each component interacts with other components. Apart from the boid rules, controlled robotic device actions such as orientation, movement, and speed are integrated into the ontology to bring about realism and visually appealing simulations. The proposed ontology was experimentally evaluated for usability and validity in the surveillance of stationary objects like buildings and dynamic targets like vehicles. The bird-bot ontology demonstrated superior performance in surveilling stationary targets when modifying the variable values of control routines (actions) compared to controlled bird-bots. In the experiments, deployment points were controlled to allow experiment repeatability. Usability was measured by quantifying the emergent behavior that emanated from applying the ontology. We looked at how closely robotic devices stayed together, how they moved in the same general direction, and how they avoided collisions. We evaluated the time it took for the bird-bots to locate the target and commence surveillance, which directly reflected the speed and quality of their emergence. We assessed whether the robotic devices maintained appropriate spacing and demonstrated avoidance behaviours, preventing overcrowding and collisions. We also assessed whether robotic devices maintained their velocities to match those of their neighbours, resulting in smooth and coordinated movement. Results indicated that the proposed ontology had causal properties. Robotic devices achieved successful area coverage with desirable efficiency and speed. Effective separation, cohesion, and alignment were observed. Properties such as fault tolerance, adaptability, and robustness emerged. To be precise, the logic in the ontology can be applied to optimise traffic flow in urban areas, highways, and transportation systems. It can inform the design of public spaces, pedestrian vii walkways, and urban layouts. This ontology can also be used to develop strategies for search and rescue operations. During natural disasters, such as earthquakes or wildfires, people often need to evacuate quickly and safely. The ontology can guide the development of evacuation plans that ensure a smooth flow of people and minimize the risk of stampedes. These features insinuate that an understanding of the ontology can aid in managing large crowds during events, protests, or gatherings. Even intriguing is the likelihood of this ontology successfully guiding the movement of autonomous vehicles or sensors in environmental monitoring tasks.