Real-time gait planning for a lower limb exoskeleton robot

2018 ◽  
pp. 193-217
Keyword(s):  
Real Time ◽  
Lower Limb ◽  
Gait Planning ◽  
Lower Limb Exoskeleton ◽  
Exoskeleton Robot

scholarly journals Estimation of the Continuous Walking Angle of Knee and Ankle (Talocrural Joint, Subtalar Joint) of a Lower-Limb Exoskeleton Robot Using a Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2807
Author(s):  
Taehoon Lee ◽  
Inwoo Kim ◽  
Soo-Hong Lee
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Lower Limb ◽  
Subtalar Joint ◽  
Walking Speed ◽  
Knee Angle ◽  
Talocrural Joint ◽  
Angle Estimation ◽  
Lower Limb Exoskeleton ◽  
Exoskeleton Robot

A lower-limb exoskeleton robot identifies the wearer′s walking intention and assists the walking movement through mechanical force; thus, it is important to be able to identify the wearer′s movement in real-time. Measurement of the angle of the knee and ankle can be difficult in the case of patients who cannot move the lower-limb joint properly. Therefore, in this study, the knee angle as well as the angles of the talocrural and subtalar joints of the ankle were estimated during walking by applying the neural network to two inertial measurement unit (IMU) sensors attached to the thigh and shank. First, for angle estimation, the gyroscope and accelerometer data of the IMU sensor were obtained while walking at a treadmill speed of 1 to 2.5 km/h while wearing an exoskeleton robot. The weights according to each walking speed were calculated using a neural network algorithm programmed in MATLAB software. Second, an appropriate weight was selected according to the walking speed through the IMU data, and the knee angle and the angles of the talocrural and subtalar joints of the ankle were estimated in real-time during walking through a feedforward neural network using the IMU data received in real-time. We confirmed that the angle estimation error was accurately estimated as 1.69° ± 1.43 (mean absolute error (MAE) ± standard deviation (SD)) for the knee joint, 1.29° ± 1.01 for the talocrural joint, and 0.82° ± 0.69 for the subtalar joint. Therefore, the proposed algorithm has potential for gait rehabilitation as it addresses the difficulty of estimating angles of lower extremity patients using torque and EMG sensors.

scholarly journals A fast parameterized gait planning method for a lower-limb exoskeleton robot

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141989322 ◽  
Author(s):  
Hao Ren ◽  
Wanfeng Shang ◽  
Niannian Li ◽  
Xinyu Wu
Keyword(s):  
Lower Limb ◽  
Planning Process ◽  
Planning Method ◽  
Planning System ◽  
Gait Planning ◽  
Lower Limb Exoskeleton ◽  
Inverted Pendulum Model ◽  
Exoskeleton Robot ◽  
Dynamic Motion Planning ◽  
Application Requirements

In order to meet requirements of diverse activities of exoskeleton robot in practical application, a dynamic motion planning system is proposed using a fast parameterized gait planning method in this article. This method can plan the required gait data by adaptively adjusting very few parameters according to different application requirements. The inverted pendulum model is used to ensure the sagittal stability of the robot in the planning process. And this article specifies the end location of robot and iterates the associated joint angles by inverse kinematics. The gait trajectories generated by the proposed method are applied to the lightweight lower-limb exoskeleton robot. The results demonstrate that the trajectories of gait can be online generated smoothly and correctly, meanwhile every variable step can be satisfied as expected.

Design of M-G modal space sliding mode control for lower limb exoskeleton robot driven by electrical actuators

Mechatronics ◽  
2021 ◽  
Vol 78 ◽  
pp. 102610
Author(s):  
Jinsong Zhao ◽  
Tao Yang ◽  
Zhilei Ma ◽  
Chifu Yang ◽  
Zhipeng Wang ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Lower Limb ◽  
Sliding Mode ◽  
Lower Limb Exoskeleton ◽  
Mode Control ◽  
Exoskeleton Robot ◽  
Modal Space

Trajectory following control of lower limb exoskeleton robot based on Udwadia–Kalaba theory

2021 ◽  
pp. 107754632110317
Author(s):  
Jin Tian ◽  
Liang Yuan ◽  
Wendong Xiao ◽  
Teng Ran ◽  
Li He
Keyword(s):  
Lower Limb ◽  
Control Method ◽  
Uniform Boundedness ◽  
Adaptive Robust Control ◽  
Structural Vibration ◽  
Control Approach ◽  
Lower Limb Exoskeleton ◽  
Exoskeleton Robot ◽  
Constraint Problem ◽  
Trajectory Following

The main objective of this article is to solve the trajectory following problem for lower limb exoskeleton robot by using a novel adaptive robust control method. The uncertainties are considered in lower limb exoskeleton robot system which include initial condition offset, joint resistance, structural vibration, and environmental interferences. They are time-varying and have unknown boundaries. We express the trajectory following problem as a servo constraint problem. In contrast to conventional control methods, Udwadia–Kalaba theory does not make any linearization or approximations. Udwadia–Kalaba theory is adopted to derive the closed-form constrained equation of motion and design the proposed control. We also put forward an adaptive law as a performance index whose type is leakage. The proposed control approach ensures the uniform boundedness and uniform ultimate boundedness of the lower limb exoskeleton robot which are demonstrated via the Lyapunov method. Finally, simulation results have shown the tracking effect of the approach presented in this article.

Adaptive Learning Inertia Control of Lower Limb Exoskeleton Robot.

2021 ◽  
Author(s):  
Muhammad Arsalan ◽  
Muhammad Tufail ◽  
SG Khan ◽  
Syed Humayoon Shah
Keyword(s):  
Adaptive Learning ◽  
Lower Limb ◽  
Lower Limb Exoskeleton ◽  
Exoskeleton Robot ◽  
Inertia Control
Sign in / Sign up

Export Citation Format

Share Document