Safe Consensus of Cooperative Manipulation with Hierarchical Event-Triggered Control Barrier Functions
This work provides a method for safer and more efficient cooperative manipulation for robotics engineers, particularly in scenarios with heavy or bulky payloads and limited resources.
This paper addresses the challenge of cooperative manipulation by multiple robots, focusing on coordinated formation tracking and safety under communication and computation constraints. The authors developed a distributed control framework using hierarchical event-triggered control barrier functions, which achieved higher precision cooperation and substantially reduced computational cost and communication frequency compared to baseline methods.
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.