Design of a Formation Control System to Assist Human Operators in Flying a Swarm of Robotic Blimps

Formation control is essential for swarm robotics, enabling coordinated behavior in complex environments. In this paper, we introduce a novel formation control system for an indoor blimp swarm using a specialized leader-follower approach enhanced with a dynamic leader-switching mechanism. This strategy allows any blimp to take on the leader role, distributing maneuvering demands across the swarm and enhancing overall formation stability. Only the leader blimp is manually controlled by a human operator, while follower blimps use onboard monocular cameras and a laser altimeter for relative position and altitude estimation. A leader-switching scheme is proposed to assist the human operator to maintain stability of the swarm, especially when a sharp turn is performed. Experimental results confirm that the leader-switching mechanism effectively maintains stable formations and adapts to dynamic indoor environments while assisting human operator.

MineLand: Simulating Large-Scale Multi-Agent Interactions with Limited Multimodal Senses and Physical Needs

Conventional multi-agent simulators often assume perfect information and limitless capabilities, hindering the ecological validity of social interactions. We propose a multi-agent Minecraft simulator, MineLand, that bridges this gap by introducing limited multimodal senses and physical needs. Our simulator supports up to 48 agents with limited visual, auditory, and environmental awareness, forcing them to actively communicate and collaborate to fulfill physical needs like food and resources. This fosters dynamic and valid multi-agent interactions. We further introduce an AI agent framework, Alex, inspired by multitasking theory, enabling agents to handle intricate coordination and scheduling. Our experiments demonstrate that the simulator, the corresponding benchmark, and the AI agent framework contribute to more ecological and nuanced collective behavior. The source code of MineLand and Alex is openly available at https://github.com/cocacola-lab/MineLand.