Sitting, Standing and Walking Control of the Series-Parallel Hybrid Recupera-Reha Exoskeleton

TL;DR

This paper introduces an advanced control method for a complex series-parallel hybrid exoskeleton, enabling realistic sitting, standing, and walking motions through optimal trajectory generation and constraint management.

Contribution

It presents a novel optimal control approach that effectively handles the complex kinematic constraints of a hybrid exoskeleton for realistic motion control.

Findings

Successful trajectory generation for sitting, standing, and walking

Effective handling of 148 degrees of freedom and loop constraints

Experimental validation of motion accuracy and feasibility

Abstract

This paper presents advancements in the functionalities of the Recupera-Reha lower extremity exoskeleton robot. The exoskeleton features a series-parallel hybrid design characterized by multiple kinematic loops resulting in 148 degrees of freedom in its spanning tree and 102 independent loop closure constraints, which poses significant challenges for modeling and control. To address these challenges, we applied an optimal control approach to generate feasible trajectories such as sitting, standing, and static walking, and tested these trajectories on the exoskeleton robot. Our method efficiently solves the optimal control problem using a serial abstraction of the model to generate trajectories. It then utilizes the full series-parallel hybrid model, which takes all the kinematic loop constraints into account to generate the final actuator commands. The experimental results demonstrate the effectiveness of our approach in generating the desired motions for the exoskeleton.