This work explores a collaborative method for ensuring safety in multi-agent formation control problems. We formulate a control barrier function (CBF) based safety filter control law for a generic distributed formation controller and extend our previously developed collaborative safety framework to an obstacle avoidance problem for agents with acceleration control inputs. We then incorporate multi-obstacle collision avoidance into the collaborative safety framework. This framework includes a method for computing the maximum capability of agents to satisfy their individual safety requirements. We analyze the convergence rate of our collaborative safety algorithm, and prove the linear-time convergence of cooperating agents to a jointly feasible safe action for all agents under the special case of a tree-structured communication network with a single obstacle for each agent. We illustrate the analytical results via simulation on a mass-spring kinematics-based formation controller and demonstrate the finite-time convergence of the collaborative safety algorithm in the simple proven case, the more general case of a fully-connected system with multiple static obstacles, and with dynamic obstacles.

翻译：本文研究了一种确保多智能体编队控制问题安全性的协作方法。我们为通用分布式编队控制器构建了基于控制屏障函数（CBF）的安全滤波器控制律，并将先前开发的协作安全框架扩展到具有加速度控制输入的智能体避障问题中。随后，我们将多障碍物碰撞避免纳入该协作安全框架。该框架包含一种计算智能体满足其个体安全需求最大能力的方法。我们分析了协作安全算法的收敛速率，并在特殊情况下（即每个智能体仅面对单个障碍物且通信网络为树状结构）证明了协作智能体线性时间收敛于对所有智能体联合可行的安全动作。我们通过基于质量-弹簧运动学的编队控制器仿真验证了分析结果，并在简单已证明情况、具有多个静态障碍物的全连接系统更一般情况以及动态障碍物场景下，展示了协作安全算法的有限时间收敛性。