The safe control of multi-robot swarms is a challenging and active field of research, where common goals include maintaining group cohesion while simultaneously avoiding obstacles and inter-agent collision. Building off our previously developed theory for distributed collaborative safety-critical control for networked dynamic systems, we propose a distributed algorithm for the formation control of robot swarms given individual agent dynamics, induced formation dynamics, and local neighborhood position and velocity information within a defined sensing radius for each agent. Individual safety guarantees for each agent are obtained using rounds of communication between neighbors to restrict unsafe control actions among cooperating agents through safety conditions derived from high-order control barrier functions (CBFs). We provide conditions under which a swarm is guaranteed to achieve collective safety with respect to multiple obstacles using a modified collaborative safety algorithm. We demonstrate the performance of our distributed algorithm via simulation in a simplified physics-based environment.

翻译：多机器人集群的安全控制是一个具有挑战性的活跃研究领域，其常见目标包括在保持群体凝聚力的同时避免障碍物和智能体间碰撞。基于我们先前针对网络化动态系统提出的分布式协同安全关键控制理论，本文提出了一种分布式算法，用于在给定单个智能体动力学、诱导编队动力学以及每个智能体定义传感半径内的局部邻域位置和速度信息条件下，实现机器人集群的编队控制。通过邻居智能体间的多轮通信，利用由高阶控制障碍函数（CBFs）推导的安全性条件限制合作智能体中的不安全控制行为，为每个智能体提供了个体安全保障。我们给出了采用改进的协同安全算法时，集群针对多个障碍物实现集体安全性的充分条件。最后通过简化物理环境仿真验证了所提分布式算法的性能。