Morphing Swarm Coordination for Autonomous Queen Tracking in Complex Hive Environments

Interacting with social insects within their natural environments requires robotic systems that are adaptive, precise, and minimally disruptive. Based on the queen tracking framework and swarm coordination algorithm developed in our previous studies, a new coordination method is proposed for adaptive formation of the multi-arm manipulator in the observation hive, as it faces different complexities in the crowded combs. To address this, a morphing mechanism is proposed to dynamically allow the swarm to shrink and expand to manoeuvre through narrow pathways in a complex environment. Moreover, the leader-follower approach is incorporated to guide the swarm towards the goal position. The simulation results demonstrate that our system achieves reliable queen-following behaviour while avoiding collisions in several scenarios. The system's robustness is evaluated against measurement noise by using the Monte-Carlo method.