Adaptive impedance control for robot-aided rehabilitation of ankle movements

Ibarra, Juan Carlos Pérez; Santos, Wilian M. dos; Krebs, Hermano Igo; Siqueira, Adriano A. G.

doi:10.1109/biorob.2014.6913854

Cited by 25 publications

(9 citation statements)

References 9 publications

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“…Thus, we assume that the use of optimal control methods in rehabilitation robotics is well-suited to assisting an impaired CNS. This assumption is consistent with previous studies, such as Hunt et al (1999) who used optimal control theory in a feedback balance control mechanism to maintain standing of paraplegic subjects, Emken et al (2005) who considered rehabilitation robot training as an optimization problem and designed an optimal controller for assist-as-needed (active-assisted) therapy, Ibarra et al (2014) and Ibarra et al (2015) who developed an optimal controller for ankle rehabilitation, Mombaur (2016) who uses optimal control theory to predict natural (healthy human) movement and improve the device performance in rehabilitation technologies, Wang et al (2017) who used optimal control to maintain patient's safety and comfort during elbow rehabilitation, and Corra et al (2017) who implemented optimal control to adjust the gains of a controller for arm rehabilitation.…”

Section: Motivationsupporting

confidence: 87%

Configuration-Dependent Optimal Impedance Control of an Upper Extremity Stroke Rehabilitation Manipulandum

2018

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Section: Motivationsupporting

confidence: 87%

Configuration-Dependent Optimal Impedance Control of an Upper Extremity Stroke Rehabilitation Manipulandum

2018

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“…In a rehabilitation process, the most suitable human cooperative results are achieved when the robot aims to reach the best movement performance while making the subject’s voluntary effort maximum and the robot output minimum (Ibarra et al, 2014 ). It can be seen from Figure 12 that once the subjects started behaving actively during the movement, the robot-generated joint pulling forces decreased, which indicates that the proposed control scheme is capable of providing adjustable assistance according to the participant’s contributed active effort.…”

Section: Experiments and Results Discussionmentioning

confidence: 99%

“…A typical ARBOT with three translational and three rotational degrees of freedom (DoFs), Rutgers Ankle, is driven by electric cylinders (Deutsch et al, 2001 ). Anklebot (Interactive Motion Technologies, Inc., USA) is a newly developed ARBOT driven by two linear actuators mounted in parallel and can actuate two DOFs, including ankle dorsi/plantar flexion and inversion/eversion (IE) (Ibarra et al, 2014 ). Saglia et al also presented a high-performance ARBOT with two rotational DOFs driven by DC motors (Saglia et al, 2013 ).…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles

Liu

Meng

et al. 2017

Front. Neurorobot.

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Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint. A new hierarchical compliance control structure, including a low-level compliance adjustment controller in joint space and a high-level admittance controller in task space, is designed. An adaptive compliance control paradigm is further developed by taking into account patient’s active contribution and movement ability during a previous period of time, in order to provide robot assistance only when it is necessarily required. Experiments on healthy and impaired human subjects were conducted to verify the adaptive hierarchical compliance control scheme. The results show that the robot hierarchical compliance can be online adjusted according to the participant’s assessment. The robot reduces its assistance output when participants contribute more and vice versa, thus providing a potentially feasible solution to the patient-in-loop cooperative training strategy.

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“…Medicine is an area that has benefited from the use of robots in help and assistance for the elderly people, rehabilitation therapies, surgeries, etc. (Hagn et al, 2008;Marchal-Crespo and Reinkensmeyer, 2009;Xu et al, 2011;Gribovskaya et al, 2011;Sharifi et al, 2012;Hussain et al, 2013;Pérez-Ibarra et al, 2014;Sharifi et al, 2014;Song et al, 2015;Li et al, 2017). In this kind of applications, safety is an important factor due to the unstructured nature of human-robot interaction tasks, and then suitable control algorithms are required to regulate a compliant and stable behavior of the robot.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Impedance Control of Robot Manipulators with Parametric Uncertainty for Constrained Path–Tracking

Bonilla

Mendoza

Campos-Delgado

et al. 2018

International Journal of Applied Mathematics and Computer Science

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The main impedance control schemes in the task space require accurate knowledge of the kinematics and dynamics of the robotic system to be controlled. In order to eliminate this dependence and preserve the structure of this kind of algorithms, this paper presents an adaptive impedance control approach to robot manipulators with kinematic and dynamic parametric uncertainty. The proposed scheme is an inverse dynamics control law that leads to the closed-loop system having a PD structure whose equilibrium point converges asymptotically to zero according to the formal stability analysis in the Lyapunov sense. In addition, the general structure of the scheme is composed of continuous functions and includes the modeling of most of the physical phenomena present in the dynamics of the robotic system. The main feature of this control scheme is that it allows precise path tracking in both free and constrained spaces (if the robot is in contact with the environment). The proper behavior of the closed-loop system is validated using a two degree-of-freedom robotic arm. For this benchmark good results were obtained and the control objective was achieved despite neglecting non modeled dynamics, such as viscous and Coulomb friction.

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Adaptive impedance control for robot-aided rehabilitation of ankle movements

Cited by 25 publications

References 9 publications

Configuration-Dependent Optimal Impedance Control of an Upper Extremity Stroke Rehabilitation Manipulandum

Configuration-Dependent Optimal Impedance Control of an Upper Extremity Stroke Rehabilitation Manipulandum

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles

Adaptive Impedance Control of Robot Manipulators with Parametric Uncertainty for Constrained Path–Tracking

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