Analysis of Aggregation Behavior of Swarm Robotics Inspired by Temperature Source

Aggregation behavior is one of the fundamental behaviors widely observed in social insects and animals. In the field of robotics, the aggregation behavior of swarm robots refers to the gathering of robots dispersed in the environment to form a cohesive unit. This behavior can be categorized into two types: self-organized aggregation and cue-based aggregation. Cue-based aggregation involves environmental cues indicating the optimal aggregation area, while self-organized aggregation does not rely on cues. This paper focuses on clue-based aggregation behavior, examining the impact of individual robot factors (movement speed and sensing range) and environmental factors (size and intensity of the cue) on aggregation behavior using the classical aggregation algorithm BEECLUST. Simulation experiments confirm the effectiveness of the algorithm in forming aggregation and the degree of influence of various factors on it. The main conclusions are as follows: Moderate increase of sensing range and forward speed significantly reduces the aggregation time, while too large sensing range may introduce some obstacle avoidance problems, affecting the aggregation effect. High-speed robots form large aggregates in a short time, but too fast a speed may lead to collisions and instability. In addition, the size and intensity of the temperature source have a significant effect on the aggregation scale. In the experiments, it was observed that larger temperature sources attract more robots, accelerating the formation of clusters. Additionally, an increase in temperature source intensity positively influences the cluster size, but it requires a balance between attraction and avoiding excessive competition.