Cooperative transport and manipulation of heavy or bulky payloads by multiple manipulators requires coordinated formation tracking, while simultaneously enforcing strict safety constraints in varying environments with limited communication and real-time computation budgets. This paper presents a distributed control framework that achieves consensus coordination with safety guarantees via hierarchical event-triggered control barrier functions (CBFs). We first develop a consensus-based protocol that relies solely on local neighbor information to enforce both translational and rotational consistency in task space. Building on this coordination layer, we propose a three-level hierarchical event-triggered safety architecture with CBFs, which is integrated with a risk-aware leader selection and smooth switching strategy to reduce online computation. The proposed approach is validated through real-world hardware experiments using two Franka manipulators operating with static obstacles, as well as comprehensive simulations demonstrating scalable multi-arm cooperation with dynamic obstacles. Results demonstrate higher precision cooperation under strict safety constraints, achieving substantially reduced computational cost and communication frequency compared to baseline methods.

翻译：多机械臂协同搬运重型或大型负载需要在有限通信和实时计算资源的动态环境中，既实现协调的编队跟踪，又同时满足严格的安全约束。本文提出一种分布式控制框架，通过分层事件触发控制屏障函数实现具有安全保障的共识协调。我们首先设计了一种仅依赖局部邻域信息的共识协议，用于在任务空间中同时保持平移与旋转一致性。基于此协调层，我们提出具有CBF的三层分层事件触发安全架构，并结合风险感知的领导者选择与平滑切换策略以降低在线计算负担。通过两台Franka机械臂在静态障碍环境中的实际硬件实验，以及动态障碍场景下可扩展多臂协同的综合仿真，验证了所提方法的有效性。结果表明，在严格安全约束下实现了更高精度的协同操作，与基准方法相比显著降低了计算成本与通信频率。