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Event-triggered adaptive backstepping admittance control for cooperative manipulation

This paper proposes an adaptive control strategy for multiple uncertain manipulators handling an object cooperatively in the presence of environmental forces and limited communication. To address the same, external and internal admittance models are imposed between the object/environment and manipulators/object to limit the excess interaction and internal forces. Thereafter, an adaptive backstepping approach is dedicated to follow the admittance-generated trajectory and deal with the dynamic uncertainties of the manipulators. Based on the Lyapunov analysis, an event-triggered (ET) mechanism is further designed to alleviate the controller-to-robot communication burden and preserve the system stability in the cooperative task. The performance of the proposed controller is compared with two admittance-based control strategies while manipulating the object through circular and lemniscate trajectories. The well-known triggering conditions, fixed and relative thresholds, are utilized further to investigate the effectiveness of the designed triggering condition. The obtained results prove the superiority of the proposed controller over the different time-triggered and even-triggered control strategies.