Synthesis and Analysis of a Chebyschev’s Straight Line Four-Bar Linkage for Generating a Minimum Jerk Velocity Profile

2014 ◽  
Author(s):  
Evagoras G. Xydas
Keyword(s):  
Velocity Profile ◽  
Kinematic Chain ◽  
Mechanical Constraints ◽  
Minimum Jerk ◽  
Straight Line ◽  
Wide Range ◽  
Spatio Temporal ◽  
Line Trajectory ◽  
Four Bar Linkage ◽  
Input Torque

The interaction between human and passive, constraint-based path generating mechanisms has been scarcely studied. When it comes to rehabilitation robots, output trajectories and/or forces are achieved mainly as a result of actuation on all joints, since they form an open kinematic chain. On the other end, there exists a wide range of mechanisms that can trace complex trajectories primarily due to mechanical constraints in their topology and structure. Probably the simplest example is the four bar linkage, a widely used 1-DOF mechanism. It consists of a driving link, a driven link, and a coupler which connects the two. As the input link rotates, each point on the coupler link traces a unique trajectory in space, called a coupler curve. Ideally, the linkage dimensions can be chosen so that a near-natural hand trajectory is generated for a specific task. As a first step, in this work a straight line generating four-bar mechanism, namely the Chebyshev’s linkage is considered for generating a natural bell-shaped velocity profile, as prescribed by the Minimum-Jerk-Model. Initially the mechanism is synthesized for producing a straight line trajectory of a desired length. Kinematic and kinetostatic analysis is performed in order to determine the required input torque necessary for achieving the desired spatio-temporal profile. The main objective is to determine whether this input torque can approximated by a series of linear torsional springs that can be installed on the pivoted side of the input link.

Flexibility in Upper Limb Rehabilitation With the Use of 1-DOF Fourbar Linkages

2018 ◽  
Author(s):  
Sabit Kurmashev ◽  
Sayat Ospanov ◽  
Aryslan Malik ◽  
Evagoras Xydas ◽  
Andreas Mueller
Keyword(s):  
Hand Rehabilitation ◽  
Upper Limb Rehabilitation ◽  
Kinematic Chains ◽  
Minimum Jerk ◽  
Community Based Rehabilitation ◽  
Straight Line ◽  
It Support ◽  
Temporal And Spatial Characteristics ◽  
Limb Rehabilitation ◽  
Four Bar Linkage

In robotic rehabilitation the interaction is usually implemented by means of robots based on multi-Degree of Freedom (DOF) open kinematic chains. Despite their inherent flexibility these machines are expensive, complex and require routine maintenance and IT support. In contrast, mechanisms based on closed kinematic chains and especially 1-DOF four- and six bar linkages are simple, yet capable of generating paths with complex kinematic characteristics. These mechanisms are preferable when simplicity and cost are the major criteria, for example in the case of community-based rehabilitation in developing countries. On the other hand, rehabilitation using 1-DOF limits flexibility and potentially impairs the exercise effectiveness, since the patient does not have access to a variety of kinematic challenges. Nevertheless, by careful ergonomic design and by considering varying time constraints, link rotation ranges and varying link lengths this limitation can be overcome. This work aims to demonstrate the potential of 1-DOF four-bar linkages to provide flexibility in therapy by considering a Hoeken’s straight line four-bar linkage. After the mechanism is dimensioned, a previously developed method is employed for establishing a final prototype design which accounts for significant neurophysiological models such as Minimum Jerk Model, Fitts’s Law and Just Noticeable Differences. Given the mechanism characteristics, its potential for generation of exercises that vary with respect to temporal and spatial characteristics is demonstrated.

scholarly journals Kinematic Analysis of Lower Limb Joint Asymmetry during Gait in People with Multiple Sclerosis

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 598
Author(s):  
Massimiliano Pau ◽  
Bruno Leban ◽  
Michela Deidda ◽  
Federica Putzolu ◽  
Micaela Porta ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Lower Limb ◽  
Sagittal Plane ◽  
Cross Sectional Study ◽  
Camera Motion ◽  
Cross Sectional ◽  
Temporal Parameters ◽  
Wide Range ◽  
Edss Score ◽  
Spatio Temporal

The majority of people with Multiple Sclerosis (pwMS), report lower limb motor dysfunctions, which may relevantly affect postural control, gait and a wide range of activities of daily living. While it is quite common to observe a different impact of the disease on the two limbs (i.e., one of them is more affected), less clear are the effects of such asymmetry on gait performance. The present retrospective cross-sectional study aimed to characterize the magnitude of interlimb asymmetry in pwMS, particularly as regards the joint kinematics, using parameters derived from angle-angle diagrams. To this end, we analyzed gait patterns of 101 pwMS (55 women, 46 men, mean age 46.3, average Expanded Disability Status Scale (EDSS) score 3.5, range 1–6.5) and 81 unaffected individuals age- and sex-matched who underwent 3D computerized gait analysis carried out using an eight-camera motion capture system. Spatio-temporal parameters and kinematics in the sagittal plane at hip, knee and ankle joints were considered for the analysis. The angular trends of left and right sides were processed to build synchronized angle–angle diagrams (cyclograms) for each joint, and symmetry was assessed by computing several geometrical features such as area, orientation and Trend Symmetry. Based on cyclogram orientation and Trend Symmetry, the results show that pwMS exhibit significantly greater asymmetry in all three joints with respect to unaffected individuals. In particular, orientation values were as follows: 5.1 of pwMS vs. 1.6 of unaffected individuals at hip joint, 7.0 vs. 1.5 at knee and 6.4 vs. 3.0 at ankle (p < 0.001 in all cases), while for Trend Symmetry we obtained at hip 1.7 of pwMS vs. 0.3 of unaffected individuals, 4.2 vs. 0.5 at knee and 8.5 vs. 1.5 at ankle (p < 0.001 in all cases). Moreover, the same parameters were sensitive enough to discriminate individuals of different disability levels. With few exceptions, all the calculated symmetry parameters were found significantly correlated with the main spatio-temporal parameters of gait and the EDSS score. In particular, large correlations were detected between Trend Symmetry and gait speed (with rho values in the range of –0.58 to –0.63 depending on the considered joint, p < 0.001) and between Trend Symmetry and EDSS score (rho = 0.62 to 0.69, p < 0.001). Such results suggest not only that MS is associated with significantly marked interlimb asymmetry during gait but also that such asymmetry worsens as the disease progresses and that it has a relevant impact on gait performances.

Forest path condition monitoring based on crowd-based trajectory data analysis

2020 ◽  
pp. 1-18
Author(s):  
Francisco Arcas-Tunez ◽  
Fernando Terroso-Saenz
Keyword(s):  
Information Acquisition ◽  
Road Network ◽  
Road Networks ◽  
Trajectory Data ◽  
Country Road ◽  
Wide Range ◽  
Sport Activities ◽  
Path Condition ◽  
Spatio Temporal ◽  
The City

The development of Road Information Acquisition Systems (RIASs) based on the Mobile Crowdsensing (MCS) paradigm has been widely studied for the last years. In that sense, most of the existing MCS-based RIASs focus on urban road networks and assume a car-based scenario. However, there exist a scarcity of approaches that pay attention to rural and country road networks. In that sense, forest paths are used for a wide range of recreational and sport activities by many different people and they can be also affected by different problems or obstacles blocking them. As a result, this work introduces SAMARITAN, a framework for rural-road network monitoring based on MCS. SAMARITAN analyzes the spatio-temporal trajectories from cyclists extracted from the fitness application Strava so as to uncover potential obstacles in a target road network. The framework has been evaluated in a real-world network of forest paths in the city of Cieza (Spain) showing quite promising results.

Experimental Investigation of Subsonic Turbulent Flow Over Single and Double Backward Facing Steps

1962 ◽  
Vol 84 (3) ◽  
pp. 317-325 ◽  
Author(s):  
D. E. Abbott ◽  
S. J. Kline
Keyword(s):  
Experimental Investigation ◽  
Velocity Profile ◽  
Flow Pattern ◽  
Reynolds Numbers ◽  
Area Ratio ◽  
Single Step ◽  
Reattachment Length ◽  
Double Step ◽  
Wide Range ◽  
Geometric Variables

Results are presented for flow patterns over backward facing steps covering a wide range of geometric variables. Velocity profile measurements are given for both single and double steps. The stall region is shown to consist of a complex pattern involving three distinct regions. The double step contains an assymmetry for large expansions, but approaches the single-step configuration with symmetric stall regions for small values of area ratio. No effect on flow pattern or reattachment length is found for a wide range of Reynolds numbers and turbulence intensities, provided the flow is fully turbulent before the step.

Synthesis and Balancing of Cam-Modulated Linkages

1987 ◽  
Author(s):  
P. Pracht ◽  
P. Minotti ◽  
M. Dahan
Keyword(s):  
Systematic Approach ◽  
Kinematic Chain ◽  
Path Generation ◽  
Industrial Manipulator ◽  
High Speeds ◽  
Structural Error ◽  
Mass Balancing ◽  
Four Bar Linkage ◽  
Robotic Applications ◽  
Class Of Functions

Abstract Linkages are inherently light, inexpensive, strong, adaptable to high speeds and have little friction. Moreover the class of functions suitable for linkage representation is large. For all these reasons numerous recent works deal with the problem of design mechanisms for robotic applications, but very often in terms of components such as gripper, transmission, balancing. We investigate a new application for linkages, using them to design industrial manipulator. The selected mechanism for this application is a four bar linkage with an adjustable lengh for exact path generation. This adjustment is performed by a track or cam which is substituted to a bar. By this mean, we define a cam-modulated linkage which possess superior accuracy potential and is capable of accomodating of industrial design restrictions. Such a kinematic chain is free from structural error for path generation and the presence of the track introduces the flexibility and versality in the usefull four bar chain. The synthesis technique of cam modulated linkage utilizes loop closure equations, envelop theory to find the centerline and the profile of the track. These techniques provide a systematic approach to the design of mechanism for path generation when extreme accuracy is required. In order to complete an contribution, we take in consideration the static balancing of the synthesized manipulator. To achieve static mass balancing we use the potential energy storage capabilities of linear springs, and integrated it with the non-linear motion of mechanism to provide an exact value of the desired counter loading functions. Examples are worked to demonstrate applications of these procedures and to illustrate the industrial potential of spring balancing and cam-modulated linkage.

Predicting Human Mobility with Reinforcement-Learning-Based Long-Term Periodicity Modeling

2021 ◽  
Vol 12 (6) ◽  
pp. 1-23
Author(s):  
Shuo Tao ◽  
Jingang Jiang ◽  
Defu Lian ◽  
Kai Zheng ◽  
Enhong Chen
Keyword(s):  
Reinforcement Learning ◽  
Human Mobility ◽  
Recurrent Network ◽  
Mobility Prediction ◽  
Learning Framework ◽  
Temporal Features ◽  
Wide Range ◽  
Spatio Temporal ◽  
Historical Trajectory

Mobility prediction plays an important role in a wide range of location-based applications and services. However, there are three problems in the existing literature: (1) explicit high-order interactions of spatio-temporal features are not systemically modeled; (2) most existing algorithms place attention mechanisms on top of recurrent network, so they can not allow for full parallelism and are inferior to self-attention for capturing long-range dependence; (3) most literature does not make good use of long-term historical information and do not effectively model the long-term periodicity of users. To this end, we propose MoveNet and RLMoveNet. MoveNet is a self-attention-based sequential model, predicting each user’s next destination based on her most recent visits and historical trajectory. MoveNet first introduces a cross-based learning framework for modeling feature interactions. With self-attention on both the most recent visits and historical trajectory, MoveNet can use an attention mechanism to capture the user’s long-term regularity in a more efficient way. Based on MoveNet, to model long-term periodicity more effectively, we add the reinforcement learning layer and named RLMoveNet. RLMoveNet regards the human mobility prediction as a reinforcement learning problem, using the reinforcement learning layer as the regularization part to drive the model to pay attention to the behavior with periodic actions, which can help us make the algorithm more effective. We evaluate both of them with three real-world mobility datasets. MoveNet outperforms the state-of-the-art mobility predictor by around 10% in terms of accuracy, and simultaneously achieves faster convergence and over 4x training speedup. Moreover, RLMoveNet achieves higher prediction accuracy than MoveNet, which proves that modeling periodicity explicitly from the perspective of reinforcement learning is more effective.

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