Interaction force control for robotic manipulators in contact tasks via prescribed performance-enhanced impedance regulation

Purpose Interaction force control is crucial for robotic manipulators in contact tasks. For different tasks, robotic manipulators are expected to possess adaptive capability to modulate interaction force performance. To this end, this paper aims to propose an interaction force control scheme for robotic contact tasks via prescribed performance-enhanced impedance regulation. Design/methodology/approach The proposed scheme integrates Dual Prescribed Performance boundary in impedance outer loop and position inner loop in parallel, named DPP-IC. Based on the performance boundary, the interaction force deviation is transformed into matching position adjustment compensation for enhancing impedance regulation in contact tasks. The compensation together with the output of the standard impedance model is then used as desired input in our designed prescribed performance PID controller (PPC-PID) in position loop. This can confine interaction force within prescribed performance boundary, thereby simultaneously improving transient and steady-state control performance. Findings Comparison experiments with three mainstream impedance control methods of standard impedance control, adaptive law-based impedance control and learning-based variable impedance control are conducted on our self-designed robotic manipulators. The results of this study prove that the advantages of the proposed scheme in improving interaction force control. Originality/value This paper first introduces prescribed performance boundary into standard impedance model in parallel, improving inter-action force control performance for robotic contact tasks on a wide range of environmental stiffness.