Hybrid oscillator-based no-delay hip exoskeleton control for free walking assistance

Purpose Walking-aid exoskeletons can assist and protect effectively the group with lower limb muscle strength decline, workers, first responders and military personnel. However, there is almost no united control strategy that can effectively assist daily walking. This paper aims to propose a hybrid oscillators’ (HOs) model to adapt to irregular gait (IG) patterns (frequent alternation between walking and standing or rapid changing of walking speed, etc.) and generate compliant and no-delay assistive torque. Design/methodology/approach The proposed algorithm, HOs, combines adaptive oscillators (AOs) with phase oscillator through switching assistive mode depending on whether or not the AOs' predicting error of hip joint degree is exceeded our expectation. HOs can compensate for delay by predicting gait phase when in AOs mode. Several treadmill and free walking experiments are designed to test the adaptability and effectiveness of HOs model under IG. Findings The experimental results show that the assistive strategy based on the HOs is effective under IG patterns, and delay is compensated totally under quasiperiodic gait conditions where a smoother human–robot interaction (HRI) force and the reduction of HRI force peak are observed. Delay compensation is found very effective at improving the performance of the assistive exoskeleton. Originality/value A novel algorithm is proposed to improve the adaptability of a walking assist hip exoskeleton in daily walking as well as generate compliant, no-delay assistive torque when converging.

[1]  Andrea Parri,et al.  An oscillator-based smooth real-time estimate of gait phase for wearable robotics , 2016, Autonomous Robots.

[2]  Pratik Kunapuli,et al.  Real-Time Neural Network-Based Gait Phase Estimation Using a Robotic Hip Exoskeleton , 2020, IEEE Transactions on Medical Robotics and Bionics.

[3]  Tao Xue,et al.  Adaptive Oscillator-Based Robust Control for Flexible Hip Assistive Exoskeleton , 2019, IEEE Robotics and Automation Letters.

[4]  Nicola Vitiello,et al.  Real-Time Estimate of Velocity and Acceleration of Quasi-Periodic Signals Using Adaptive Oscillators , 2013, IEEE Transactions on Robotics.

[5]  Jongwon Lee,et al.  Adaptive Oscillator-Based Control for Active Lower-Limb Exoskeleton and its Metabolic Impact , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[6]  Junwon Jang,et al.  Delayed Output Feedback Control for Gait Assistance With a Robotic Hip Exoskeleton , 2019, IEEE Transactions on Robotics.

[7]  Bahram Tarvirdizadeh,et al.  Design and fabrication of a lower limb exoskeleton to assist in stair ascending , 2019, Ind. Robot.

[8]  Thomas G. Sugar,et al.  Nonlinear, Phase-Based Oscillator to Generate and Assist Periodic Motions , 2016 .

[9]  Daniel P. Ferris,et al.  Invariant hip moment pattern while walking with a robotic hip exoskeleton. , 2011, Journal of biomechanics.

[10]  Hui Li,et al.  Synthesis and experiment of a lower limb exoskeleton rehabilitation robot , 2017, Ind. Robot.

[11]  Scott Kuindersma,et al.  Human-in-the-loop optimization of hip assistance with a soft exosuit during walking , 2018, Science Robotics.

[12]  M. Grimmer,et al.  A Novel Approach for Gait Phase Estimation for different Locomotion Modes using Kinematic Shank Information , 2020 .

[13]  Rachel W Jackson,et al.  Human-in-the-loop optimization of exoskeleton assistance during walking , 2017, Science.

[14]  Conor J. Walsh,et al.  A Lightweight and Efficient Portable Soft Exosuit for Paretic Ankle Assistance in Walking After Stroke , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[15]  Robert D. Gregg,et al.  Continuous-Phase Control of a Powered Knee–Ankle Prosthesis: Amputee Experiments Across Speeds and Inclines , 2018, IEEE Transactions on Robotics.

[16]  Jason Kerestes,et al.  Limit Cycles to Enhance Human Performance Based on Phase Oscillators , 2015 .

[17]  Yong He,et al.  Locomotion Mode Identification and Gait Phase Estimation for Exoskeletons During Continuous Multilocomotion Tasks , 2021, IEEE Transactions on Cognitive and Developmental Systems.

[18]  Jason Kerestes,et al.  Adding and Subtracting Energy to Body Motion: Phase Oscillator , 2014 .

[19]  Jean-Sébastien Plante,et al.  Design and Control of a Multifunctional Ankle Exoskeleton Powered by Magnetorheological Actuators to Assist Walking, Jumping, and Landing , 2019, IEEE Robotics and Automation Letters.

[20]  Youngbo Shim,et al.  A new adaptive frequency oscillator for gait assistance , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[21]  Andrea Parri,et al.  Gait Phase Estimation Based on Noncontact Capacitive Sensing and Adaptive Oscillators , 2017, IEEE Transactions on Biomedical Engineering.

[22]  Jusuk Lee,et al.  Fully autonomous hip exoskeleton saves metabolic cost of walking , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[23]  Andrew Long,et al.  Autonomous multi-joint soft exosuit with augmentation-power-based control parameter tuning reduces energy cost of loaded walking , 2018, Journal of NeuroEngineering and Rehabilitation.

[24]  Conor J. Walsh,et al.  IMU-based iterative control for hip extension assistance with a soft exosuit , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[25]  Jusuk Lee,et al.  RNN-Based On-Line Continuous Gait Phase Estimation from Shank-Mounted IMUs to Control Ankle Exoskeletons , 2019, 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR).

[26]  Thomas G. Sugar,et al.  Nonlinear, Phase-Based Oscillator to Generate and Assist Periodic Motions , 2017 .