Flocking is a social animals’ common behaviour observed in nature. It has a great potential for real-world applications such as exploration in agri-robotics using low-cost robotic solutions. In this paper, an extended model of a self-organised flocking mechanism using heterogeneous swarm system is proposed. The proposed model for swarm robotic systems is a combination of a collective motion mechanism with obstacle avoidance functions, which ensures a collision-free flocking trajectory for the followers. An optimal control model for the leader is also developed to steer the swarm to a desired goal location. Compared to the conventional methods, by using the proposed model, the swarm network has less requirement for power and storage. The feasibility of the proposed self-organised flocking algorithm is validated by realistic robotic simulation software.

群居是自然界中观察到的一种群居动物的常见行为。它在现实世界的应用中具有巨大的潜力，例如使用低成本机器人解决方案探索农业机器人。在本文中，提出了一种使用异构群系统的自组织集群机制的扩展模型。所提出的群体机器人系统模型是集体运动机制与避障功能的结合，确保了跟随者的无碰撞聚集轨迹。还开发了领导者的最佳控制模型，以将群体引导到所需的目标位置。与传统方法相比，通过使用所提出的模型，群网络对电力和存储的要求更低。