Human Gait Trajectory Learning Using Online Gaussian Process for Assistive Lower Limb Exoskeleton

Long, Yi; Du, Zhijiang; Dong, Wei; Wang, Weidong

doi:10.1007/978-981-10-2404-7_14

Cited by 7 publications

(4 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, evolving system has been incorporated into learning compliance control of exoskeletons. Long et al 120 put forward an evolving learning control based on SGPR. Motion trajectories of exoskeletons were learned online using SGPR, whose parameters were optimized by the conjugate gradient method, when receiving the interaction force and joint angles of human as the inputs.…”

Section: Compliance Controlmentioning

confidence: 99%

A review on human intent understanding and compliance control strategies for lower limb exoskeletons

Yang

Shi

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

The exoskeleton has emerged as a promising technology to enhance humans’ strength and boost users’ efficiency. In order to provide congruent human–machine interaction for assisting the users, exoskeletons should have knowledge of human’s planned action and accordingly command the robot by the designed controller. It means the ubiquitous aspect of exoskeletons lies on motion intent understanding and active compliance control. In the last decade, extensive research has been conducted on the two topics. However, no major breakthrough has been made. Thus, a systematic review and analysis on this very subject is of great significance in developing exoskeletons. Within this context, this review first surveys the history of lower limb exoskeletons to summarize the various technologies for realizing transparent human exoskeleton coordination. Then, an overview about motion intent understanding and compliance control strategies are presented in detail. Furthermore, the future trend and research directions are also outlined.

show abstract

Section: Compliance Controlmentioning

confidence: 99%

A review on human intent understanding and compliance control strategies for lower limb exoskeletons

Yang

Shi

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

show abstract

“…The distributed forward model learning proposed in this paper aims to lower the computational burden by explicitly applying several subsets of the training data. In the past five years, the sparse Gaussian process has been widely used in spatiotemporal modeling [ 39 ] as well as robotics reinforcement learning [ 40 ]. However, it is inconceivable to use sparse approximations with a data set size of

[ 41 ].…”

Section: Evolving Internal Model Controlmentioning

confidence: 99%

Intrinsic Sensing and Evolving Internal Model Control of Compact Elastic Module for a Lower Extremity Exoskeleton

Wang

Dong

et al. 2018

Sensors

Self Cite

View full text Add to dashboard Cite

To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human–robot interaction sensing and compliant control, respectively. According to the intrinsic sensing properties of the elastic module, in this paper, only one compact elastic module is applied to realize both purposes. Thus, the corresponding control strategy is required and evolving internal model control is proposed to address this issue. Moreover, the input signal to the controller is derived from the deflection of the compact elastic module. The human–robot interaction is considered as the disturbance which is approximated by the output error between the exoskeleton control plant and evolving forward learning model. Finally, to verify our proposed control scheme, several experiments are conducted with our robotic exoskeleton system. The experiment shows a satisfying result and promising application feasibility.

show abstract

“…For obvious acceptability of exoskeleton suites in the industries, the exoskeleton should be capable of assisting its wearer to walk normally without impeding the wearer’s natural movement nor forcing the wearer into unintended motion [ 9 ]. A control technology that will enable the exoskeleton to learn or predict a wearer’s movement for synchronous walking assistance can be seen as one of the important requirement in exoskeleton technology for industrial manual handling applications [ 10 – 12 ].…”

Section: Introductionmentioning

confidence: 99%

Exoskeleton robot control for synchronous walking assistance in repetitive manual handling works based on dual unscented Kalman filter

et al. 2018

View full text Add to dashboard Cite

Prolong walking is a notable risk factor for work-related lower-limb disorders (WRLLD) in industries such as agriculture, construction, service profession, healthcare and retail works. It is one of the common causes of lower limb fatigue or muscular exhaustion leading to poor balance and fall. Exoskeleton technology is seen as a modern strategy to assist worker’s in these professions to minimize or eliminate the risk of WRLLDs. Exoskeleton has potentials to benefit workers in prolong walking (amongst others) by augmenting their strength, increasing their endurance, and minimizing high muscular activation, resulting in overall work efficiency and productivity. Controlling exoskeleton to achieve this purpose for able-bodied personnel without impeding their natural movement is, however, challenging. In this study, we propose a control strategy that integrates a Dual Unscented Kalman Filter (DUKF) for trajectory generation/prediction of the spatio-temporal features of human walking (i.e. joint position, and velocity, and acceleration) and an impedance cum supervisory controller to enable the exoskeleton to follow this trajectory to synchronize with the human walking. Experiment is conducted with four subjects carrying a load and walking at their normal speed- a typical scenario in industries. EMG signals taken at two muscles: Right Vastus Intermedius (on the thigh) and Right Gastrocnemius (on the calf) indicated reduction in muscular activation during the experiment. The results also show the ability of the control system to predict spatio-temporal features of the pilots’ walking and to enable the exoskeleton to move in concert with the pilot.

show abstract

Human Gait Trajectory Learning Using Online Gaussian Process for Assistive Lower Limb Exoskeleton

Cited by 7 publications

References 27 publications

A review on human intent understanding and compliance control strategies for lower limb exoskeletons

A review on human intent understanding and compliance control strategies for lower limb exoskeletons

Intrinsic Sensing and Evolving Internal Model Control of Compact Elastic Module for a Lower Extremity Exoskeleton

Exoskeleton robot control for synchronous walking assistance in repetitive manual handling works based on dual unscented Kalman filter

Contact Info

Product

Resources

About