scholarly journals Shoulder kinematics plus contextual target information enable control of multiple distal joints of a simulated prosthetic arm and hand

Author(s):  
Sébastien Mick ◽  
Effie Segas ◽  
Lucas Dure ◽  
Christophe Halgand ◽  
Jenny Benois-Pineau ◽  
...  

Abstract Background Prosthetic restoration of reach and grasp function after a trans-humeral amputation requires control of multiple distal degrees of freedom in elbow, wrist and fingers. However, such a high level of amputation reduces the amount of available myoelectric and kinematic information from the residual limb. Methods To overcome these limits, we added contextual information about the target’s location and orientation such as can now be extracted from gaze tracking by computer vision tools. For the task of picking and placing a bottle in various positions and orientations in a 3D virtual scene, we trained artificial neural networks to predict postures of an intact subject’s elbow, forearm and wrist (4 degrees of freedom) either solely from shoulder kinematics or with additional knowledge of the movement goal. Subjects then performed the same tasks in the virtual scene with distal joints predicted from the context-aware network. Results Average movement times of 1.22s were only slightly longer than the naturally controlled movements (0.82 s). When using a kinematic-only network, movement times were much longer (2.31s) and compensatory movements from trunk and shoulder were much larger. Integrating contextual information also gave rise to motor synergies closer to natural joint coordination. Conclusions Although notable challenges remain before applying the proposed control scheme to a real-world prosthesis, our study shows that adding contextual information to command signals greatly improves prediction of distal joint angles for prosthetic control.

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Randall T. Fawcett ◽  
Abhishek Pandala ◽  
Jeeseop Kim ◽  
Kaveh Akbari Hamed

Abstract The primary goal of this paper is to develop a formal foundation to design nonlinear feedback control algorithms that intrinsically couple legged robots with bio-inspired tails for robust locomotion in the presence of external disturbances. We present a hierarchical control scheme in which a high-level and real-time path planner, based on an event-based model predictive control (MPC), computes the optimal motion of the center of mass (COM) and tail trajectories. The MPC framework is developed for an innovative reduced-order linear inverted pendulum (LIP) model that is augmented with the tail dynamics. At the lower level of the control scheme, a nonlinear controller is implemented through the use of quadratic programming (QP) and virtual constraints to force the full-order dynamical model to track the prescribed optimal trajectories of the COM and tail while maintaining feasible ground reaction forces at the leg ends. The potential of the analytical results is numerically verified on a full-order simulation model of a quadrupedal robot augmented with a tail with a total of 20 degrees-of-freedom. The numerical studies demonstrate that the proposed control scheme coupled with the tail dynamics can significantly reduce the effect of external disturbances during quadrupedal locomotion.


Author(s):  
RAHUL R. KALIKI ◽  
RAHMAN DAVOODI ◽  
GERALD E. LOEB

Patients with transhumeral amputations and C5/C6 quadriplegia may be able to use voluntary shoulder motion as command signals for powered prostheses and functional electrical stimulation, respectively. Spatiotemporal synergies exist between the shoulder and elbow joints for goal-oriented reaching movements as performed by able-bodied subjects. We are using a multi-layer perceptron neural network to discover and embody these synergies. Such a network could be used as a high-level controller that could predict the desired distal arm joint kinematics from the voluntary movements of the shoulder joint of an able-bodied subject. We evaluated this for a task that involved reaching to 16 targets in a horizontal plane. After reaching reasonable offline prediction accuracy for our neural networks, we then deployed the best network to make real-time predictions of the elbow angles and examined its performance on both inter- and intra-subject trials. Finally, we extended the model to utilize the five degrees-of-freedom at the shoulder to control the five degrees-of-freedom required for a prosthetic arm and hand to reach and grasp variously oriented objects in the extrapersonal workspace. Such a system, although very simple, was readily controllable for a reach and grasp task presented to the subject in a virtual reality environment.


Author(s):  
Yuhong Liu ◽  
Anthony Dutoi

<div> <div>A shortcoming of presently available fragment-based methods is that electron correlation (if included) is described at the level of individual electrons, resulting in many redundant evaluations of the electronic relaxations associated with any given fluctuation. A generalized variant of coupled-cluster (CC) theory is described, wherein the degrees of freedom are fluctuations of fragments between internally correlated states. The effects of intra-fragment correlation on the inter-fragment interaction is pre-computed and permanently folded into the effective Hamiltonian. This article provides a high-level description of the CC variant, establishing some useful notation, and it demonstrates the advantage of the proposed paradigm numerically on model systems. A companion article shows that the electronic Hamiltonian of real systems may always be cast in the form demanded. This framework opens a promising path to build finely tunable systematically improvable methods to capture precise properties of systems interacting with a large number of other systems. </div> </div>


2017 ◽  
Author(s):  
Yuhong Liu ◽  
Anthony Dutoi

<div> <div>A shortcoming of presently available fragment-based methods is that electron correlation (if included) is described at the level of individual electrons, resulting in many redundant evaluations of the electronic relaxations associated with any given fluctuation. A generalized variant of coupled-cluster (CC) theory is described, wherein the degrees of freedom are fluctuations of fragments between internally correlated states. The effects of intra-fragment correlation on the inter-fragment interaction is pre-computed and permanently folded into the effective Hamiltonian. This article provides a high-level description of the CC variant, establishing some useful notation, and it demonstrates the advantage of the proposed paradigm numerically on model systems. A companion article shows that the electronic Hamiltonian of real systems may always be cast in the form demanded. This framework opens a promising path to build finely tunable systematically improvable methods to capture precise properties of systems interacting with a large number of other systems. </div> </div>


Author(s):  
Afef Hfaiedh ◽  
Ahmed Chemori ◽  
Afef Abdelkrim

In this paper, the control problem of a class I of underactuated mechanical systems (UMSs) is addressed. The considered class includes nonlinear UMSs with two degrees of freedom and one control input. Firstly, we propose the design of a robust integral of the sign of the error (RISE) control law, adequate for this special class. Based on a change of coordinates, the dynamics is transformed into a strict-feedback (SF) form. A Lyapunov-based technique is then employed to prove the asymptotic stability of the resulting closed-loop system. Numerical simulation results show the robustness and performance of the original RISE toward parametric uncertainties and disturbance rejection. A comparative study with a conventional sliding mode control reveals a significant robustness improvement with the proposed original RISE controller. However, in real-time experiments, the amplification of the measurement noise is a major problem. It has an impact on the behaviour of the motor and reduces the performance of the system. To deal with this issue, we propose to estimate the velocity using the robust Levant differentiator instead of the numerical derivative. Real-time experiments were performed on the testbed of the inertia wheel inverted pendulum to demonstrate the relevance of the proposed observer-based RISE control scheme. The obtained real-time experimental results and the obtained evaluation indices show clearly a better performance of the proposed observer-based RISE approach compared to the sliding mode and the original RISE controllers.


Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 137
Author(s):  
Larisa Dunai ◽  
Martin Novak ◽  
Carmen García Espert

The present paper describes the development of a prosthetic hand based on human hand anatomy. The hand phalanges are printed with 3D printing with Polylactic Acid material. One of the main contributions is the investigation on the prosthetic hand joins; the proposed design enables one to create personalized joins that provide the prosthetic hand a high level of movement by increasing the degrees of freedom of the fingers. Moreover, the driven wire tendons show a progressive grasping movement, being the friction of the tendons with the phalanges very low. Another important point is the use of force sensitive resistors (FSR) for simulating the hand touch pressure. These are used for the grasping stop simulating touch pressure of the fingers. Surface Electromyogram (EMG) sensors allow the user to control the prosthetic hand-grasping start. Their use may provide the prosthetic hand the possibility of the classification of the hand movements. The practical results included in the paper prove the importance of the soft joins for the object manipulation and to get adapted to the object surface. Finally, the force sensitive sensors allow the prosthesis to actuate more naturally by adding conditions and classifications to the Electromyogram sensor.


2018 ◽  
Vol 36 (6) ◽  
pp. 1114-1134 ◽  
Author(s):  
Xiufeng Cheng ◽  
Jinqing Yang ◽  
Lixin Xia

PurposeThis paper aims to propose an extensible, service-oriented framework for context-aware data acquisition, description, interpretation and reasoning, which facilitates the development of mobile applications that provide a context-awareness service.Design/methodology/approachFirst, the authors propose the context data reasoning framework (CDRFM) for generating service-oriented contextual information. Then they used this framework to composite mobile sensor data into low-level contextual information. Finally, the authors exploited some high-level contextual information that can be inferred from the formatted low-level contextual information using particular inference rules.FindingsThe authors take “user behavior patterns” as an exemplary context information generation schema in their experimental study. The results reveal that the optimization of service can be guided by the implicit, high-level context information inside user behavior logs. They also prove the validity of the authors’ framework.Research limitations/implicationsFurther research will add more variety of sensor data. Furthermore, to validate the effectiveness of our framework, more reasoning rules need to be performed. Therefore, the authors may implement more algorithms in the framework to acquire more comprehensive context information.Practical implicationsCDRFM expands the context-awareness framework of previous research and unifies the procedures of acquiring, describing, modeling, reasoning and discovering implicit context information for mobile service providers.Social implicationsSupport the service-oriented context-awareness function in application design and related development in commercial mobile software industry.Originality/valueExtant researches on context awareness rarely considered the generation contextual information for service providers. The CDRFM can be used to generate valuable contextual information by implementing more reasoning rules.


Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3099 ◽  
Author(s):  
Cheng Zhao ◽  
Li Sun ◽  
Pulak Purkait ◽  
Tom Duckett ◽  
Rustam Stolkin

In this paper, a novel Pixel-Voxel network is proposed for dense 3D semantic mapping, which can perform dense 3D mapping while simultaneously recognizing and labelling the semantic category each point in the 3D map. In our approach, we fully leverage the advantages of different modalities. That is, the PixelNet can learn the high-level contextual information from 2D RGB images, and the VoxelNet can learn 3D geometrical shapes from the 3D point cloud. Unlike the existing architecture that fuses score maps from different modalities with equal weights, we propose a softmax weighted fusion stack that adaptively learns the varying contributions of PixelNet and VoxelNet and fuses the score maps according to their respective confidence levels. Our approach achieved competitive results on both the SUN RGB-D and NYU V2 benchmarks, while the runtime of the proposed system is boosted to around 13 Hz, enabling near-real-time performance using an i7 eight-cores PC with a single Titan X GPU.


2005 ◽  
Vol 127 (6) ◽  
pp. 934-945 ◽  
Author(s):  
Jason Potratz ◽  
Jingzhou Yang ◽  
Karim Abdel-Malek ◽  
Esteban Peña Pitarch ◽  
Nicole Grosland

This paper presents the design and prototyping of an inherently compliant lightweight hand mechanism. The hand mechanism itself has 15 degrees of freedom and five fingers. Although the degrees of freedom in each finger are coupled, reducing the number of independent degrees of freedom to 5, the 15 degrees of freedom of the hand could potentially be individually actuated. Each joint consists of a novel flexing mechanism that is based on the loading of a compression spring in the axial and transverse direction via a cable and conduit system. Currently, a bench top version of the prototype is being developed; the three joints of each finger are coupled together to simplify the control system. The current control scheme under investigation simulates a control scheme where myoelectric signals in the wrist flexor and extensor muscles are converted in to x and y coordinates on a control scheme chart. Static load-deformation analysis of finger segments is studied based on a 3-dimensional model without taking the stiffener into account, and the experiment validates the simulation.


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