Estimation of Desired Motion Intention and compliance control for upper limb assist exoskeleton

Khan, Abdul Manan; Yun, Doo-Hee; Zuhaib, Khalil Muhammad; Iqbal, Junaid; Yan, Rui-Jun; Khan, Fatima; Han, Changsoo

doi:10.1007/s12555-015-0151-7

Cited by 26 publications

(14 citation statements)

References 41 publications

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“…Generally, guidance for the motion of the manipulator is obtained via a wrist-mounted force sensor which evaluates the forces exerted by the human operators. The most commonly used method to convert these measurements into kinematic instructions to the robot is through compliance control, which establishes a direct relationship between the measured forces and the changes in the robot position [7,8,9]. Yet other variants and methods can be found in the literature.…”

Section: Literature Reviewmentioning

confidence: 99%

Human–robot collaboration for safe object transportation using force feedback

Solanes

Gracia

Muñoz-Benavent

et al. 2018

Robotics and Autonomous Systems

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This work presents an approach based on multi-task, non-conventional sliding mode control and admittance control for human-robot collaboration aimed at handling applications using force feedback. The proposed robot controller is based on three tasks with different priority levels in order to cooperatively perform the safe transportation of an object with a human operator. In particular, a high-priority task is developed using non-conventional sliding mode control to guarantee safe reference parameters imposed by the task, e.g., keeping a load at a desired orientation (to prevent spill out in the case of liquids, or to reduce undue stresses that may compromise fragile items). Moreover, a second task based on a hybrid admittance control algorithm is used for the human operator to guide the robot by means of a force sensor located at the robot tool. Finally, a third low-priority task is considered for redundant robots in order to use the remaining degrees of freedom of the robot to achieve a pre-set secondary goal (e.g., singularity avoidance, remaining close to a homing configuration for increased safety, etc.) by means of the gradient projection method. The main advantages of the proposed method are robustness and low computational cost. The applicability and effectiveness of the proposed approach is substantiated by experimental results using a redundant 7R manipulator: the Sawyer collaborative robot.

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Section: Literature Reviewmentioning

confidence: 99%

Human–robot collaboration for safe object transportation using force feedback

Solanes

Gracia

Muñoz-Benavent

et al. 2018

Robotics and Autonomous Systems

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“…In practical implementation, the control strategies applied in rehabilitation robots directly determine the performance of robot-assisted rehabilitation training [18]. Currently, the existing rehabilitation control schemes can be classified into two types according to the participation degree of patients, i.e., the passive training control strategies [19]- [21] for the patients at the acute period to passively conduct repetitive movement tasks along predefined trajectory, and the cooperative training control strategies [22]- [26] for the patients at the recovery period to be actively engaged in the therapy training program. In [27], a passive training control approach combined with neuron proportion-integral and feedforward compensation control was developed to reduce the trajectory tracking error of a pneumatic muscles-driven rehabilitation robot.…”

Section: Introductionmentioning

confidence: 99%

Integral Fuzzy Sliding Mode Impedance Control of an Upper Extremity Rehabilitation Robot Using Time Delay Estimation

Dawen

Chen

et al. 2019

IEEE Access

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Robot-assisted cooperative rehabilitation training has shown superiority in helping the individuals with motion impairment problems to regain their motor functions. This paper presents the development and evaluation of a new cooperative training control scheme for an end-effector-type rehabilitation robot to provide upper extremity rehabilitation training with desired compliance and intensity. Firstly, the overall mechanical structure and real-time control system of rehabilitation robot are introduced. Secondly, an integral fuzzy sliding mode impedance control strategy combined with time-delay estimation (IFSMIC-TDE) is proposed to induce the active participation of patients and suppress impedance error. The IFSMIC-TDE approach is free from nonlinear robot dynamics, and it is designed to be robust to the external uncertainties and inherent chattering characteristics. After that, the closed-loop system stability with IFSMIC-TDE is proved based on the Lyapunov stability theory. Finally, experimental investigations are conducted to illustrate the effectiveness of the proposed rehabilitation robot and control algorithm. The comparison results indicate that the proposed IFSMIC-TDE can achieve better control performance and less impedance error. Besides, the interaction compliance and training intensity can be qualitatively adjusted via appropriate impedance parameters. INDEX TERMS Upper extremity rehabilitation robot, cooperative training, sliding mode impedance control, fuzzy turner, time delay estimation.

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“…The most commonly used method to convert these measurements into kinematic instructions to the robot is through compliance control, which establishes a direct relationship between the measured forces and the changes in the robot position [7,8]. Yet other variants and methods can be found in the literature.…”

Section: Introductionmentioning

confidence: 99%

Human-robot cooperation for robust surface treatment using non-conventional sliding mode control

et al. 2018

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This work presents a human-robot closely collaborative solution to cooperatively perform surface treatment tasks such as polishing, grinding, deburring, etc. The method considers two force sensors attached to the manipulator end-effector and tool: one sensor is used to properly accomplish the surface treatment task, while the second one is used by the operator to guide the robot tool. The proposed scheme is based on task priority and adaptive non-conventional sliding mode control. The applicability of the proposed approach is substantiated by experimental results using a redundant 7R manipulator: the Sawyer cobot.

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Estimation of Desired Motion Intention and compliance control for upper limb assist exoskeleton

Cited by 26 publications

References 41 publications

Human–robot collaboration for safe object transportation using force feedback

Human–robot collaboration for safe object transportation using force feedback

Integral Fuzzy Sliding Mode Impedance Control of an Upper Extremity Rehabilitation Robot Using Time Delay Estimation

Human-robot cooperation for robust surface treatment using non-conventional sliding mode control

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