Dynamic modelling and predictive position/force control of a plant-inspired growing robot

This paper presents the development and control of a dynamic model for a plant-inspired growing robot, termed the 'vine-robot', using the Euler-Lagrangian method. The unique growth mechanism of the vine-robot enables it to navigate complex environments by extending its body. We derive the dynamic equations of motion and employ model predictive control to regulate the task space position, orientation, and interaction forces. Simulation experiments are conducted to evaluate the performance of the proposed model and control strategy. The results demonstrate that the model effectively achieves sub-millimeter precision in the position control in both static and time varying refrence trajectroies, and sub micronewton in force control.