Three-dimensional asymmetric maximum weight lifting prediction considering dynamic joint strength

2021 ◽  
pp. 095441192098703
Author(s):  
Rahid Zaman ◽  
Yujiang Xiang ◽  
Jazmin Cruz ◽  
James Yang
Keyword(s):  
Experimental Data ◽  
Degrees Of Freedom ◽  
Inverse Dynamics ◽  
Three Dimensional ◽  
Optimization Method ◽  
Weight Lifting ◽  
Joint Torque ◽  
Maximum Weight ◽  
Angular Velocities ◽  
Asymmetric Lifting

In this study, the three-dimensional (3D) asymmetric maximum weight lifting is predicted using an inverse-dynamics-based optimization method considering dynamic joint torque limits. The dynamic joint torque limits are functions of joint angles and angular velocities, and imposed on the hip, knee, ankle, wrist, elbow, shoulder, and lumbar spine joints. The 3D model has 40 degrees of freedom (DOFs) including 34 physical revolute joints and 6 global joints. A multi-objective optimization (MOO) problem is solved by simultaneously maximizing box weight and minimizing the sum of joint torque squares. A total of 12 male subjects were recruited to conduct maximum weight box lifting using squat-lifting strategy. Finally, the predicted lifting motion, ground reaction forces, and maximum lifting weight are validated with the experimental data. The prediction results agree well with the experimental data and the model’s predictive capability is demonstrated. This is the first study that uses MOO to predict maximum lifting weight and 3D asymmetric lifting motion while considering dynamic joint torque limits. The proposed method has the potential to prevent individuals’ risk of injury for lifting.

Three-Dimensional Symmetric Maximum Weight Lifting Prediction

2020 ◽  
Author(s):  
Rahid Zaman ◽  
Yujiang Xiang ◽  
Jazmin Cruz ◽  
James Yang
Keyword(s):  
Degrees Of Freedom ◽  
Material Handling ◽  
Inverse Dynamics ◽  
Three Dimensional ◽  
Weight Lifting ◽  
Optimization Approach ◽  
Maximum Weight ◽  
Manual Material Handling ◽  
Reaction Forces ◽  
Skeletal Model

Abstract Lifting heavy weight is one of the main reasons for manual material handling related injuries which can be mitigated by determining the limiting lifting weight of a person. In this study, a 40 degrees of freedom (DOFs) spatial skeletal model was employed to predict the symmetric maximum weight lifting motion. The lifting problem was formulated as a multi-objective optimization (MOO) problem to minimize the dynamic effort and maximize the box weight. An inverse-dynamics-based optimization approach was used to determine the optimal lifting motion and the maximum lifting weight considering dynamic joint strength. The predicted lifting motion, ground reaction forces (GRFs), and maximum box weight were shown to match well with the experimental results. It was found that for the three-dimensional (3D) symmetric lifting the left and right GRFs were not same.

Trajectory Tracking of Underactuated Multibody Systems

2011 ◽  
Author(s):  
Stefan Reichl ◽  
Wolfgang Steiner
Keyword(s):  
Trajectory Tracking ◽  
Multibody Systems ◽  
Degrees Of Freedom ◽  
Inverse Dynamics ◽  
Feedforward Control ◽  
Equations Of Motion ◽  
Three Dimensional ◽  
Differential Algebraic Equations ◽  
State Variables ◽  
Algebraic Equations

This work presents three different approaches in inverse dynamics for the solution of trajectory tracking problems in underactuated multibody systems. Such systems are characterized by less control inputs than degrees of freedom. The first approach uses an extension of the equations of motion by geometric and control constraints. This results in index-five differential-algebraic equations. A projection method is used to reduce the systems index and the resulting equations are solved numerically. The second method is a flatness-based feedforward control design. Input and state variables can be parameterized by the flat outputs and their time derivatives up to a certain order. The third approach uses an optimal control algorithm which is based on the minimization of a cost functional including system outputs and desired trajectory. It has to be distinguished between direct and indirect methods. These specific methods are applied to an underactuated planar crane and a three-dimensional rotary crane.

scholarly journals A three-dimensional musculoskeletal model of the dog

2020 ◽  
Author(s):  
Heiko Stark ◽  
Martin S. Fischer ◽  
Alexander Hunt ◽  
Fletcher Young ◽  
Roger Quinn ◽  
...  
Keyword(s):  
Experimental Data ◽  
Body Size ◽  
Degrees Of Freedom ◽  
Inverse Dynamics ◽  
Musculoskeletal Model ◽  
Muscle Synergy ◽  
Locomotor System ◽  
Wide Range ◽  
Joint Load

AbstractDogs are an interesting object of investigation because of the wide range of body size, body mass, and physique. In the last several years, the number of clinical and biomechanical studies on dog locomotion has increased. However, the relationship between body structure and joint load during locomotion, as well as between joint load and degenerative diseases of the locomotor system (e.g. dysplasia), are not sufficiently understood. In vivo measurements/records of joint forces and loads or deep/small muscles are complex, invasive, and sometimes ethically questionable. The use of detailed musculoskeletal models may help in filling that knowledge gap. We describe here the methods we used to create a detailed musculoskeletal model with 84 degrees of freedom and 134 muscles. Our model has three key-features: Three-dimensionality, scalability, and modularity. We tested the validity of the model by identifying forelimb muscle synergies of a beagle at walk. We used inverse dynamics and static optimization to estimate muscle activations based on experimental data. We identified three muscle synergy groups by using hierarchical clustering. Predicted activation patterns exhibited good agreement with experimental data for most of the forelimb muscles. We expect that our model will speed up the analysis of how body size, physique, agility, and disease influence joint neuronal control and loading in dog locomotion.

scholarly journals Single Task Optimization-Based Planar Box Delivery Motion Simulation and Experimental Validation

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Yujiang Xiang ◽  
Shadman Tahmid ◽  
Paul Owens ◽  
James Yang
Keyword(s):  
Joint Angle ◽  
Inverse Dynamics ◽  
Optimization Method ◽  
Joint Torque ◽  
Motion Simulation ◽  
Single Task ◽  
Joint Torques ◽  
Time Integral ◽  
Design Variables ◽  
Complicated Task

Abstract Box delivery is a complicated task and it is challenging to predict the box delivery motion associated with the box weight, delivering speed, and location. This paper presents a single task-based inverse dynamics optimization method for determining the planar symmetric optimal box delivery motion (multi-task jobs). The design variables are cubic B-spline control points of joint angle profiles. The objective function is dynamic effort, i.e., the time integral of the square of all normalized joint torques. The optimization problem includes various constraints. Joint angle profiles are validated through experimental results using root-mean-square-error (RMSE) and Pearson’s correlation coefficient. This research provides a practical guidance to prevent injury risks in joint torque space for workers who lift and deliver heavy objects in their daily jobs.

Three-Dimensional Symmetric Maximum Weight Lifting Prediction

2021 ◽  
Author(s):  
G M Rahid Uz Zaman Rana ◽  
Yujiang Xiang ◽  
Jazmin Cruz ◽  
James Yang
Keyword(s):  
Three Dimensional ◽  
Weight Lifting ◽  
Maximum Weight

Development of a Human Symbiotic Assist Arm “PAS-Arm” (Basic Concept and Mechanism)

2012 ◽  
Vol 24 (3) ◽  
pp. 458-463 ◽  
Author(s):  
Mineo Higuchi ◽  
Keyword(s):  
Basic Concept ◽  
Degrees Of Freedom ◽  
Low Cost ◽  
Three Dimensional ◽  
Physical Interaction ◽  
Assist Device ◽  
Shared Workspace ◽  
Continuously Variable Transmissions ◽  
Angular Velocities ◽  
Mechanical Constraint

We describe a new robotic assist device: a passive assist arm (PAS-Arm). PAS-Arms are intended for direct physical interaction with a human operator, handling a shared payload. PAS-Arms are physically passive. Their purpose is not to enhance human strength, but to provide virtual guiding surfaces, which constrain and guide the motion of the payload within a shared workspace. PAS-Arms have three joints and a three dimensional workspace, but possesses only a two degrees of freedom, due to the reduction of degrees of freedom created by a combination of Continuously Variable Transmissions (CVTs) and differential gears. The combination of CVTs and differential gears places one mechanical constraint on three angular velocities of the joints. PAS-Arms have no joint actuators and no force sensors. Thus they are potentially well suited to safety and low cost. This paper proposes a basic concept of PAS-Arms and explains a principle and a construction of PAS-Arms. We discuss the relation of PAS-Arms to conventionally actuated robots and another type of assist arms. We also describe range of transmission ratio of CVTs.11. This paper is the full translation from the transactions of JSME, Series C, Vol.73, No.730, 2007.

Development of a Human Symbiotic Assist Arm “PAS-Arm” (Design of Mechanism · CVT and Experimental System)

2013 ◽  
Vol 25 (1) ◽  
pp. 211-219 ◽  
Author(s):  
Mineo Higuchi ◽  
Keyword(s):  
Degrees Of Freedom ◽  
Time Derivative ◽  
Three Dimensional ◽  
Experimental System ◽  
Normal Vector ◽  
Physical Interaction ◽  
Differential Relation ◽  
Continuously Variable Transmissions ◽  
Angular Velocities ◽  
The Relationship

We describe a new robotic assist device: a passive assist arm (PAS-Arm). PAS-Arms are intended for direct physical interaction with a human operator, handling a shared payload. PAS-Arms are physically passive. Their purpose is not to enhance human strength, but to provide virtual guiding surfaces, which constrain and guide the motion of the payload within a shared workspace. PAS-Arms have three joints and a three-dimensional workspace, but possess only a two degrees of freedom, due to the reduction of degrees of freedom created by a combination of Continuously Variable Transmissions (CVTs) and differential gears. We have developed an experimental system of the PAS-Arm. In this paper, we describe kinematic specification of the experimental system. We discuss the differential relation of transmission ratios created by the CVTs. We conducted the relationship between transmission ratio resolutions of the CVTs and resolutions of normal vector of the virtual guiding surface, and the relationship between angular velocities of PAS-Arm’s joints and time derivative of the transmission ratios. Assuming that the Euclidean norm of the angular velocities is constant, maximum time derivative of transmission ratios is in proportion to link lengths of the PAS-Arm. We also describe the design of the CVT for use in the experimental system.1 1. This paper is the full translation from the transactions of JSME, Series C, Vol.75, No.749, pp. 104-112, 2009.

Muscle Force Prediction in OpenSim Using Skeleton Motion Optimization Results As Input Data

2019 ◽  
Author(s):  
Rahid Zaman ◽  
Yujiang Xiang ◽  
Ritwik Rakshit ◽  
James Yang
Keyword(s):  
Inverse Dynamics ◽  
Center Of Pressure ◽  
Integrated Approach ◽  
Optimization Method ◽  
Weight Lifting ◽  
Muscle Forces ◽  
Predictive Capability ◽  
Motion Optimization ◽  
Reaction Forces ◽  
Skeletal Model

Abstract This paper describes an integrated approach to predict human leg and spine muscle forces during lifting by integration of a predictive skeletal model with OpenSim. The two-dimensional (2D) skeletal lifting motion is first predicted by using an inverse dynamics optimization method. Then, the prediction outputs, including joint angle profiles, ground reaction forces, and center of pressure, are incorporated in OpenSim biomechanics software to analyze muscle forces for lifting. Therefore, the integrated approach has predictive capability on musculoskeletal level. By using this method, we can predict and analyze muscles forces for heavy weight lifting motion which is difficult to simulate directly using a 3D musculoskeletal model.

Performance Enhancement of Three-Dimensional Soil Structure Model via Optimization for Estimating Seismic Behavior of Buried Pipelines

2017 ◽  
Vol 11 (05) ◽  
pp. 1750019 ◽  
Author(s):  
Tsuyoshi Ichimura ◽  
Kohei Fujita ◽  
Atsushi Yoshiyuki ◽  
Pher Errol Quinay ◽  
Muneo Hori ◽  
...  
Keyword(s):  
Finite Element ◽  
Degrees Of Freedom ◽  
Performance Enhancement ◽  
Three Dimensional ◽  
Element Model ◽  
Optimization Method ◽  
Buried Pipelines ◽  
Ground Structure ◽  
3D Finite Element ◽  
Ground Structures

Damage to buried pipelines due to complex ground responses has been reported at residential development sites and valley plains with complex ground structures. Three-dimensional (3D) ground amplification analyses using 3D, nonlinear, finite-element methods may be effective in predicting such damage; however, it is often difficult to construct ground structures that are capable of reproducing observational characteristics. In this paper, we propose a 3D ground structure optimization method using a 3000[Formula: see text] forward finite-element dynamic analysis with approximately 0.27 million degrees of freedom, enabled by combining an automated 3D finite-element model-generation method and a fast 3D finite-element wave propagation analysis method. This optimization method is capable of estimating 3D ground structure models that can reproduce observational data characteristics. The effectiveness of the method is shown through an illustrative example.

Squat Lifting Motion Prediction With Heavy Load Considering Dynamic Strength of Knee Joint

2017 ◽  
Author(s):  
Rahid Zaman ◽  
Yujiang Xiang
Keyword(s):  
Knee Joint ◽  
Inverse Dynamics ◽  
Strength Function ◽  
Three Dimensional ◽  
Dynamic Strength ◽  
Joint Torque ◽  
Future Research ◽  
Heavy Load ◽  
Squat Lifting ◽  
Heavy Loads

This paper studies the knee joint dynamic strength modeling and simulation for squat lifting with heavy loads. The dynamic strength is modeled as a three-dimensional function of joint angle and velocity based on experimental isometric and isokinetic strength data. Then the dynamic strength function is formulated as joint torque limits in an inverse dynamics based optimization formulation. By using this formulation, squat lifting is predicted with heavy loads. An enumeration procedure is introduced to predict maximum lifting weight under various lifting conditions by considering dynamic strength of knee joint. In addition, the effect of lifting speed on the maximum lifting weight is investigated. Several future research directions are identified.

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