Force tracking smooth adaptive admittance control in unknown environment

Abstract

AbstractIn this research, a force tracking smoothing adaptive admittance controller is proposed that grants precise contact forces (performance necessary for many critical interaction tasks such as polishing) for unknown interaction environments (e.g., leather or thin and soft materials). First, an online indirect adaptive update strategy is proposed for generating the reference trajectory required by the desired tracking force, considering the uncertainty of the interaction. The sensor noise amplitude is environment dynamics and the necessity condition for traditional admittance controller to achieve ideal steady-state force tracking. Then, a pre-PD controller is introduced to increase the parameter convergence rate while ensuring the steady-state force tracking accuracy and enhancing the robustness of the system. The robustness boundary is also analyzed to provide assurance for the stability of the system. Finally, we verify the effectiveness of the proposed method in simulations. Simultaneously, an experiment is conducted on the AUBO-i5 serial collaborative robot, and the experimental results proved the excellent comprehensive performance of the control framework.