[Paper Review] Safe Consensus of Cooperative Manipulation with Hierarchical Event-Triggered Control Barrier Functions

Simiao Zhuang, Bingkun Huang+1 more|arXiv (Cornell University)|Mar 6, 2026

Distributed Control Multi-Agent Systems0 citations

TL;DR

This paper introduces a distributed hierarchical event-triggered control barrier function (CBF) framework to achieve safe consensus in cooperative manipulation, validated on two Franka arms with real hardware and simulations.

ABSTRACT

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.

Motivation & Objective

• Motivate safe, formation-consistent cooperative manipulation under safety constraints and limited communication.
• Develop a distributed consensus protocol that uses only local neighborhood information for task-space coordination.
• Propose a three-level hierarchical event-triggered safety architecture combined with risk-aware leader switching to reduce online computation.

Proposed method

• Formulate a consensus-based protocol enforcing translational and rotational consistency using local neighbor information in the task space.
• Linearize manipulator dynamics to a double-integrator in task space via feedback linearization; map to a distributed control input u_i.
• Introduce a three-level hierarchical event-triggered safety framework (environmental, inter-agent, intrinsic) using control barrier functions.
• Implement a damped least-squares inverse kinematics to robustly compute joint accelerations near singularities.
• Use a leader selection mechanism and switching strategy to manage environmental safety constraints while ensuring feasibility (via CBFs with Clarke subgradients when needed).

Experimental results

Research questions

• RQ1 How can distributed MAS coordination achieve asymptotic positional consensus with bounded rotational disagreement in cooperative manipulation?
• RQ2 Can hierarchical event-triggered CBFs guarantee forward invariance of safety sets under joint actuation and communication constraints?
• RQ3 What mechanisms (leader switching, null-space regulation) ensure safe, scalable manipulation with dynamic environments?
• RQ4 How does the proposed approach compare to baseline distributed CBF and centralized NMPC/MPPI in terms of safety, precision, computation, and communication?

Key findings

• The proposed HET-CBF framework achieves higher precision cooperation under safety constraints compared to baselines in experiments with two Franka manipulators.
• The method reduces online computation and communication frequency relative to baseline methods.
• An event-triggered safety approach effectively activates constraints only when needed, lowering inter-agent communication.
• A damped least-squares inverse kinematics formulation stabilizes task-space control near kinematic singularities.
• Leader switching with safety guarantees maintains feasibility during transitions between leaders.
• Real-world experiments and simulations demonstrate scalable multi-arm cooperation with obstacle-rich environments.