An Identification-Based Method Improving the Transparency of a Robotic Upper Limb Exoskeleton

Verdel, Dorian; Bastide, Simon; Vignais, Nicolas; Bruneau, Olivier; Berret, Bastien

doi:10.1017/s0263574720001459

Cited by 21 publications

(60 citation statements)

References 52 publications

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“…a) Initial force feedback control law: All the control laws used in the present study are based on an accurate compensation of the robot dynamics. This compensation is based on the methods described in [17]. Over this dynamic compensation of the robot, the FT sensor is used to build a feedback control based on the normal interaction forces with the user [46].…”

Section: B Weight Support Control Lawsmentioning

confidence: 99%

“…All these applications are conditioned by several critical functionalities including transparency [10] and the ability to compensate for the user's weight [11]. Transparency is the ability of an exoskeleton to influence human movement as little as possible when worn [12] and has already been extensively studied [13], [14], [15], [16], [17]. It is for instance critical at the end of a rehabilitation process to ensure that the robot will not lead the user to adopt abnormal motor patterns.…”

Section: Introductionmentioning

confidence: 99%

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Human Weight Compensation with a Backdrivable Upper-Limb Exoskeleton: Identification and Control

Verdel¹,

Bastide²,

Vignais³

et al. 2021

Preprint

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Active exoskeletons are promising devices for improving rehabilitation procedures in patients and preventing musculoskeletal disorders in workers. In particular, exoskeletons implementing human limb’s weight support are interesting to restore some mobility in patients with muscle weakness and help in occupational load carrying tasks. The present study aims at improving weight support of the upper limb by providing a weight model considering joint misalignments and a control law including feedforward terms learned from a prior population-based analysis. Three experiments, for design and validation purposes, are conducted on a total of 65 participants who performed posture maintenance and elbow flexion/extension movements. The introduction of joint misalignments in the weight support model significantly reduced the model errors, in terms of weight estimation, and enhanced the estimation reliability. The introduced control architecture reduced model tracking errors regardless of the condition. Weight support significantly decreased the activity of antigravity muscles, as expected, but increased the activity of elbow extensors because gravity is usually exploited by humans to accelerate a limb downwards. These findings suggest that an adaptive weight support controller could be envisioned to further minimize human effort in certain applications.

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Section: B Weight Support Control Lawsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Human Weight Compensation with a Backdrivable Upper-Limb Exoskeleton: Identification and Control

Verdel¹,

Bastide²,

Vignais³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Initial force feedback control law: All the control laws used in the present study are based on an accurate compensation of the robot dynamics. This compensation is based on the methods described in [14]. Over this dynamic compensation of the robot, the FT sensor is used to build a feedback control based on the normal interaction forces with the user [44].…”

Section: Weight Support Control Lawsmentioning

confidence: 99%

“…where τ ctrl is the control torque to apply at the elbow joint of the robot,τ i (q, φ) is the estimated WS control torque resulting from Equation ( 8), τ i is the measured interaction torque resulting from FT sensor measurements andτ comp (q,q, q) is the estimated compensation of the robot dynamics based on the model presented in [14] and in Equation ( 14). This model is dependent on q (respectivelyq and q) the angular acceleration (respectively angular velocity and position) of the elbow joint.…”

Section: Weight Support Control Lawsmentioning

confidence: 99%

“…All these applications are conditioned by several critical functionalities including transparency [7] and the ability to compensate for the user's weight [8]. Transparency is the ability of an exoskeleton to inuence human movement as little as possible when worn [9] and has already been extensively studied [10,11,12,13,14]. It is for instance critical at the end of a rehabilitation process to ensure that the robot will not lead the user to adopt abnormal motor patterns.…”

Section: Introductionmentioning

confidence: 99%

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A New Weight Compensation Model Considering Joint Misalignments Monitored by a Feedforward Impedance Control Method Applied To an Active Upper-Limb Exoskeleton

Verdel

Bastide

Vignais

et al. 2021

Preprint

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Background Active exoskeletons are promising devices for improving rehabilitation procedures in patients. In particular, exoskeletons implementing human limb's weight support (WS) are interesting to restore some mobility in patients with muscle weakness. Using active exoskeletons should result in accurate and generic WS but its effect on human motor control will critically depend on the position of the user within the exoskeleton and the characteristics of the control law. Methods The present study aims at improving WS of the upper limb by providing a weight model considering joint misalignments and a control law including feedforward terms learned from a prior population-based analysis. Three experiments are respectively conducted on 29, 17 and 19 participants who performed posture maintenance and pointing movements with the forearm in the sagittal plane. The first two experiments were used to build an accurate WS control law and the third experiment was conducted to compare the effects of different WS control laws on human movement and assess their quality. During these three experiments, kinematic data and eletromyographic activity of elbow flexors and extensors were measured. Interaction forces were measured with a force/torque sensor placed between the human segment and the robot link. Results The introduction of joint misalignments in the WS model allowed to drastically reduce the model errors in terms of weight estimation. The use of a feedforward architecture based on model and errors learned during experiments, coupled to a force feedback, allowed to reduce model tracking errors in both static and dynamic conditions during vertical movements, which induce substantial variations of gravitational torques. Overall, WS did not affect the general kinematic motion parameters of the participants and decreased the activity of antigravity muscles (flexors). However, WS increased the activation of extensors because weight is usually exploited by humans to accelerate a limb downward. Conclusion A new weight compensation model considering joint misalignments was introduced and data showed their prominent role on WS accuracy and homogeneity. Three WS control laws were compared and results indicated that classical control methods were not sufficient to provide an accurate tracking of the weight model during dynamic vertical movements but that introducing simple feedforward terms learned from previous measures could significantly improve WS accuracy. Accordingly, WS reduced significantly activity in flexors in both static and dynamic conditions. Nevertheless, WS tended to increase the activity of extensors, which might be an important factor in a rehabilitation perspective. Indeed, if the present WS control law will be very helpful to allow patients accelerating the arm upward despite some muscle weakness, it may have an opposite effect when accelerating the arm downward. A partial WS controller could thus be more appropriate in rehabilitation applications.

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Optimization of design parameters and improvement of human comfort conditions in an upper-limb exosuit for assistance

Lu,

Aoustin,

Arakelian

2024

Multibody Syst Dyn

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Exoskeleton robots have wide application in industrial field as well as for patients with locomotor disability. Among them, the exoskeleton with flexible structure, named exosuit has aroused great interest among researchers. They are usually made of soft material like cables and fabrics. Since there are no rigid frames and links in the Exosuits, they are much lighter and have less misalignment problems than the rigid exoskeletons. However, the physical human-robot interaction still remains a problem in the Exosuit design. Excessive pressure exerted by cables on soft tissues and skeleton of the human will lead to discomfort or even injuries. Besides, as assistive device, Exosuits are usually worn by users over a long period of time, which requires high energy efficiency. In this paper, based on these considerations, a multi-objective optimization approach based on swarm intelligence has been developped and applied in order to improve the physical human-robot interaction and energy efficiency performance of an upper-limb Exosuit for assistance. The optimization results have demonstrated its effectiveness in the design phase.

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An Identification-Based Method Improving the Transparency of a Robotic Upper Limb Exoskeleton

Cited by 21 publications

References 52 publications

Human Weight Compensation with a Backdrivable Upper-Limb Exoskeleton: Identification and Control

Human Weight Compensation with a Backdrivable Upper-Limb Exoskeleton: Identification and Control

A New Weight Compensation Model Considering Joint Misalignments Monitored by a Feedforward Impedance Control Method Applied To an Active Upper-Limb Exoskeleton

Optimization of design parameters and improvement of human comfort conditions in an upper-limb exosuit for assistance

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