Optimization of Dynamic Sit-to-Stand Trajectories to Assess Whole-Body Motion Performance of the Humanoid Robot REEM-C

Abstract

To enable the application of humanoid robots outside of laboratory environments, the biped must meet certain requirements. These include, in particular, coping with dynamic motions such as climbing stairs or ramps or walking over irregular terrain. Sit-to-stand transitions also belong to this category. In addition to their actual application such as getting out of vehicles or standing up after sitting, for example, at a table, these motions also provide benefits in terms of performance assessment. Therefore, they have long been used as a sports medical and geriatric assessment for humans. Here, we develop optimized sit-to-stand trajectories using optimal control, which are characterized by their dynamic and humanlike nature. We implement these motions on the humanoid robot REEM-C. Based on the obtained sensor data, we present a unified benchmarking procedure based on two different experimental protocols. These protocols are characterized by their increasing level of difficulty for quantifying different aspects of lower limb performance. We report performance results obtained by REEM-C using two categories of indicators: primary, scenario-specific indicators that assess overall performance (chair height and ankle-to-chair distance) and subsidiary, general indicators that further describe performance. The latter provide a more detailed analysis of the applied motion and are based on metrics such as the angular momentum, zero moment point, capture point, or foot placement estimator. In the process, we identify performance deficiencies of the robot based on the collected data. Thus, this work is an important step toward a unified quantification of bipedal performance in the execution of humanlike and dynamically demanding motions.

Can lower-limb exoskeletons support sit-to-stand motions in frail elderly without crutches? A study combining optimal control and motion capture

“…Optimal control is an optimization-based approach to determine the control and state trajectories over a time period, such that an objective function related to said controls and states are minimized (Siciliano et al, 2009). Since it is able to determine the required joint actuation of a recorded motion (Koch and Mombaur, 2015) and also generate an optimal trajectory (Hu and Mombaur, 2017;Mombaur and Ho Hoang, 2017;Aller et al, 2022), this method is chosen for the computational STS investigation presented. The dynamic process of interest is a person, without using crutches, performing STS with and without the TWIN exoskeleton.…”

“…The movement speed in the elderly is found to be slower than the younger population, suggesting that a stable STS does not solely rely on leg muscle strength, but also the ability to maintain stability (Yamada and Demura, 2009 ). Optimal control was utilized to determine the best way possible for external forces to support an elderly person doing STS (Mombaur and Ho Hoang, 2017 ) and the optimal trajectory for the REEM-C humanoid robot to perform unassisted STS (Aller et al, 2022 ). Recently, an impedance modulation control that accounts for balance reinforcement and impedance compensation is created to assist STS motion of a person wearing the Angeleg exoskeleton (Huo et al, 2022 ).…”