Estimating Contact Forces and Moments for Walking Robots and Exoskeletons Using Complementary Energy Methods

Vantilt, Jonas; Giraddi, Chetan; Aertbeliën, Erwin; Groote, Friedl De; Schutter, Joris De

doi:10.1109/lra.2018.2852776

Cited by 10 publications

(12 citation statements)

References 19 publications

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“…This allowed to also compensate the exoskeleton when the person moves his trunk forward while sitting on the stool. The distribution of the forces over both feet while not on the stool is performed with a model-based method [44] that account for the stiffness of the exoskeleton.…”

Section: Discussionmentioning

confidence: 99%

“…In humanoid robotics, this is solved by minimizing a weighted combination of contact forces and joint torques [26, 27]. In this paper, we use a similar method [44] in which the weights of the minimization are determined by the stiffness of the exoskeleton parts.…”

Section: Methods: Model-based Controlmentioning

confidence: 99%

“…These contact wrenches cannot be solved with the three floating base equations alone. An optimization based on the stiffness of the exoskeleton [44] is used to solve the six contact wrench components, as described in the Methods section. As the stool contact is both hard to locate and measure, it is modelled by introducing gain parameters in the dynamics, see Eq.…”

Section: Sit-to-stand Exoskeletonmentioning

confidence: 99%

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Model-based control for exoskeletons with series elastic actuators evaluated on sit-to-stand movements

Vantilt

Tanghe

Afschrift

et al. 2019

J NeuroEngineering Rehabil

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Background Currently, control of exoskeletons in rehabilitation focuses on imposing desired trajectories to promote relearning of motions. Furthermore, assistance is often provided by imposing these desired trajectories using impedance controllers. However, lower-limb exoskeletons are also a promising solution for mobility problems of individuals in daily life. To develop an assistive exoskeleton which allows the user to be autonomous, i.e. in control of his motions, remains a challenge. This paper presents a model-based control method to tackle this challenge. Methods The model-based control method utilizes a dynamic model of the exoskeleton to compensate for its own dynamics. After this compensation of the exoskeleton dynamics, the exoskeleton can provide a desired assistance to the user. While dynamic models of exoskeletons used in the literature focus on gravity compensation only, the need for modelling and monitoring of the ground contact impedes their widespread use. The control strategy proposed here relies on modelling of the full exoskeleton dynamics and of the contacts with the environment. A modelling strategy and general control scheme are introduced. Results Validation of the control method on 15 non-disabled adults performing sit-to-stand motions shows that muscle effort and joint torques are similar in the conditions with dynamically compensated exoskeleton and without exoskeleton. The condition with exoskeleton in which the compensating controller was not active showed a significant increase in human joint torques and muscle effort at the knee and hip. Motor saturation occurred during the assisted condition, which limited the assistance the exoskeleton could deliver. Conclusions This work presents the modelling steps and controller design to compensate the exoskeleton dynamics. The validation seems to indicate that the presented model-based controller is able to compensate the exoskeleton.

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Section: Discussionmentioning

confidence: 99%

Section: Methods: Model-based Controlmentioning

confidence: 99%

Section: Sit-to-stand Exoskeletonmentioning

confidence: 99%

See 1 more Smart Citation

Model-based control for exoskeletons with series elastic actuators evaluated on sit-to-stand movements

Vantilt

Tanghe

Afschrift

et al. 2019

J NeuroEngineering Rehabil

Self Cite

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“…In Reference 21, an inverse dynamics controller is used in a 2‐DOF upper‐limb robotic exoskeleton jointly with a disturbance observer which allows for estimating and compensating for perturbation torques. In Reference 22, a 6‐DOF lower‐limb robotic exoskeleton is controlled with the use of PD‐type controllers while joint torques are computed through an optimization procedure related with energy variables of the robotic mechanism, Finally, in Reference 23, a knee rehabilitation exoskeleton is considered in which sliding‐mode control is applied together with a nonlinear disturbance observer.…”

Section: Introductionmentioning

confidence: 99%

Flatness‐based disturbance observer for exoskeleton robots under time‐delayed contact forces

2022

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The article proposes flatness‐based control and a Kalman filter‐based disturbance observer for solving the control problem of a robotic exoskeleton under time‐delayed exogenous disturbances. A two‐link lower‐limb robotic exoskeleton is used as a case study. It is proven that this robotic system is differentially flat. The robot is considered to be subject to unknown contact forces at its free‐end which in turn generate unknown disturbance torques at its joints. It is shown that the dynamic model of the robotic exoskeleton can be transformed into the input–output linearized form and equivalently into the linear canonical Brunovsky form. This linearized description of the exoskeleton's dynamics is both controllable and observable. It allows for designing a stabilizing feedback controller with the use of the pole‐placement (eigenvalues assignment) method. Moreover, it allows for solving the state estimation problem with the use of Kalman Filtering (the use of the Kalman filter on the flatness‐based linearized model of nonlinear dynamical systems is also known as derivative‐free nonlinear Kalman filtering). Furthermore, (i) by extending the state vector of the exoskeleton after considering as additional state variables the additive disturbance torques which affect its joints and (ii) by redesigning the Kalman filter as a disturbance observer, one can achieve the real‐time estimation of the perturbations that affect this robotic system. Finally, by including in the controller of the exoskeleton additional terms that compensate for the estimated disturbance torques, the perturbations' effects can be eliminated and the precise tracking of reference trajectories by the joints of this robot can be ensured.

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“…11 To improve walking compliance, series elastic actuators are used in the exoskeleton with the methods of estimating contact forces and moments. 12 A motion-phasebased PID controller is designed for the lower limb exoskeletons, in which the performance of stability and robustness is verified by experiments. 13 For walking assistance, higher level demands include torque control and power-mass ratio.…”

Section: Introductionmentioning

confidence: 99%

Design on electrohydraulic servo driving system with walking assisting control for lower limb exoskeleton robot

Wang

Liang

et al. 2021

International Journal of Advanced Robotic Systems

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According to the characteristics of human gait and the requirements of power assistance, locomotive mechanisms and electrohydraulic servo driving are designed on a lower limb exoskeleton robot, in which the miniaturization and lightweight of driving system are realized. The kinematics of the robot is analyzed and verified via the typical movements of the exoskeleton. In this article, the simulation on the power of joints during level walking was analyzed in ADAMS 2016, which is a multibody simulation and motion analysis software. Motion ranges and driving strokes are then optimized. A proportional integral derivative (PID) control method with error estimation and pressure compensation is proposed to satisfy the requirements of joints power assistance and comply with the motion of human lower limb. The proposed method is implemented into the exoskeleton for assisted walking and is verified by experimental results. Finally, experiments show that the tracking accuracy and power-assisted performance of exoskeleton robot joints are improved.

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Estimating Contact Forces and Moments for Walking Robots and Exoskeletons Using Complementary Energy Methods

Cited by 10 publications

References 19 publications

Model-based control for exoskeletons with series elastic actuators evaluated on sit-to-stand movements

Model-based control for exoskeletons with series elastic actuators evaluated on sit-to-stand movements

Flatness‐based disturbance observer for exoskeleton robots under time‐delayed contact forces

Design on electrohydraulic servo driving system with walking assisting control for lower limb exoskeleton robot

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