The present study aims to propose a dynamic interactive self-organizing aggregation (DISA) method for swarm robots. The proposed method was determined by way of the movement of swarm robots, obstacle, and robot sensors. The controller used in the DISA method helps the state selector decide through the utilization of these sensors. Systematic simulations were conducted a different number of robots {10, 25, 50}, different detection radii {3, 4} and different arena sizes {40 × 40, 50 × 50, 60 × 60}. The performance of aggregation behavior was compared with other aggregation methods recommended in literature using Total Distance (TD) between robots, Cluster Metrics (CM), Expected Cluster Size (ECS) metric and aggregation completion time. Moreover, noise at different intensities was applied to sensor inputs of the robots. The robustness of the effect of increasing noise on aggregation behavior was examined comparatively. Consequently, the simulation results based on the other compared methods indicated that the utilization of the proposed DISA method led to a higher performance by 88% in the ECS and CM metric as well as in all TD metric measurements and aggregation completion time results.

本研究旨在为群体机器人提出一种动态交互式自组织聚合（DISA）方法。所提出的方法是通过群体机器人、障碍物和机器人传感器的运动来确定的。DISA 方法中使用的控制器帮助状态选择器通过利用这些传感器来做出决定。系统模拟了不同数量的机器人 {10, 25, 50}，不同的检测半径 {3, 4} 和不同的场地尺寸 {40 × 40, 50 × 50, 60 × 60}。使用机器人之间的总距离 (TD)、集群度量 (CM)、预期集群大小 (ECS) 度量和聚合完成时间，将聚合行为的性能与文献中推荐的其他聚合方法进行了比较。此外，不同强度的噪声被应用于机器人的传感器输入。比较地检查了增加噪声对聚集行为的影响的稳健性。因此，基于其他比较方法的模拟结果表明，所提出的 DISA 方法的使用使 ECS 和 CM 度量以及所有 TD 度量测量和聚合完成时间结果的性能提高了 88%。