Optimization-Based Digital Human Dynamics: Santos™ Walking Backwards

2007 ◽  
Author(s):  
Hyun Jung Kwon ◽  
Yujiang Xiang ◽  
Salam Rahmatalla ◽  
R. Timothy Marler ◽  
Karim Abdel-Malek ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Joint Angle ◽  
Spline Interpolation ◽  
Performance Measure ◽  
Degree Of Freedom ◽  
Human Model ◽  
Entire Body ◽  
Joint Torques ◽  
Digital Human

An objective of this study is to simulate the backward walking motion of a full-body digital human model. The model consists of 55 degree of freedom – 6 degrees of freedom for global translation and rotation and 49 degrees of freedom representing the kinematics of the entire body. The resultant action of all the muscles at a joint is represented by the torque for each degree of freedom. The torques and angles at a joint are treated as unknowns in the optimization problem. The B-spline interpolation is used to represent the time histories of the joint angles and the well-established robotics formulation of the Denavit-Hartenberg method is used for kinematics analysis of the mechanical system. The recursive Lagrangian formulation is used to develop the equations of motion, and was chosen because of its known computational efficiency. The backwards walking problem is formulated as a nonlinear optimization problem. The control points of the B-splines for the joint angle profiles are treated as the design variables. For the performance measure, total dynamic effort that is represented as the integral of the sum of the squares of all the joint torques is minimized using a sequential quadratic programming algorithm. The solution is simulated in the Santos™ environment. Results of the optimization problem are the torque and joint angle profiles. The torques at the key joints and the ground reaction forces are compared to those for the forward walk in order to study the differences between the two walking patterns. Simulation results are approximately validated with the experimental data which is motion captured in the VSR Lab at the University of Iowa.

Optimization-Based Prediction of Aiming and Kneeling Military Tasks Performed by a Soldier

2012 ◽  
Author(s):  
Mahdiar Hariri ◽  
Jasbir Arora ◽  
Karim Abdel-Malek
Keyword(s):  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Human Model ◽  
Ground Reaction Forces ◽  
Optimization Approach ◽  
Ground Contact ◽  
Digital Human Model ◽  
Reaction Forces ◽  
Digital Human ◽  
The Given

The objective of this study is to predict the “Aiming While Standing” and “Aiming While Kneeling” motion tasks for a soldier (human) using a full-body, three dimensional digital human model. The digital human is modeled as a 55 degree of freedom branched mechanism. Six degrees of freedom specify the global position and orientation of the coordinate frame attached to the pelvis of the digital human and 49 degrees of freedom represent the revolute joints which model the human joints and determine the kinematics of the entire digital human. Motion is generated by a multi-objective optimization approach minimizing the mechanical energy and joint discomfort simultaneously. A sequential quadratic programming (SQP) algorithm in SNOPT is used to solve the nonlinear optimization problem. The optimization problem is subject to constraints which represent the limitations of the environment, the digital human model and the motion task. Design variables are the joint angle profiles. All the forces, inertial, gravitational as well as external, are known, except the ground reaction forces. The feasibility of the generation of that arbitrary motion by using the given ground contact areas is ensured by using the well known Zero Moment Point (ZMP) constraint. During the kneeling motion, different parts of the body come in contact and lose contact with the ground which is modeled using a general approach. The ground reaction force on each transient ground contact area is determined using the equations of motion. It is assumed that enough friction exists that allow the human to generate reaction forces as determined by the ZMP constraint. Using these ground reaction forces, the required torques at all joints are calculated by the recursive Lagrangian formulation. Using the given method, we can predict realistic motions for the “Aiming While Standing” and “Aiming While Kneeling” tasks. The optimization approach is able to very well predict the “Natural Point of Aim” which is a well known concept for soldiers. In other words, the approach is able to predict the most comfortable final orientation of the feet on the ground for engaging a specific target. We also predict cases where the orientation of the soldier’s feet are enforced. Many virtual experiments have been conducted by changing the target location in the 3D space, changing the anthropometry of the soldier, adding armor to different joints, changing the variable parameters of the rifle, adding backpack and using different weapons.

Effect of Foot Location on Human Running Prediction

2014 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Rajan Bhatt ◽  
Yujiang Xiang ◽  
Jasbir S. Arora ◽  
Karim Abdel-Malek
Keyword(s):  
Degrees Of Freedom ◽  
Reaction Force ◽  
Performance Measure ◽  
Joint Torque ◽  
Upper Body ◽  
Human Model ◽  
Digital Human Model ◽  
Digital Human ◽  
Dynamics Method ◽  
Human Running

Human running is simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). A predictive dynamics method is used to formulate the running problem, and normal running is formulated as a symmetric and cyclic motion. The dynamic effort and impulse are used as the performance measure, and the upper body yawing moment is also included in the performance measure. The joint angle profiles and joint torque profiles are calculated for the full-body human model, and the ground reaction force is determined. The effect of foot location on the running motion prediction are simulated and studied.

Human Carrying Simulation With Symmetric and Asymmetric Loads

2012 ◽  
Author(s):  
Yujiang Xiang ◽  
Jasbir S. Arora ◽  
Salam Rahmatalla ◽  
Hyun-Joon Chung ◽  
Rajan Bhatt ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Human Motion ◽  
Human Model ◽  
Physical Constraints ◽  
Digital Human Model ◽  
Load Carrying ◽  
Reaction Forces ◽  
Asymmetric Load ◽  
Optimization Schemes ◽  
Digital Human

Human carrying is simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). Predictive dynamics approach is used to predict the carrying motion with symmetric and asymmetric loads. In this process, the model predicts joints dynamics using optimization schemes and task-based physical constraints. The results indicated that the model can realistically match human motion and ground reaction forces data during symmetric and asymmetric load carrying task. With such prediction capability the model could be used for biomedical and ergonomic studies.

WORKSPACE OF DIGITAL HUMAN LOWER EXTREMITIES

2009 ◽  
Vol 06 (02) ◽  
pp. 291-306 ◽  
Author(s):  
JINGZHOU (JAMES) YANG
Keyword(s):  
Degrees Of Freedom ◽  
Virtual Prototyping ◽  
Lower Extremities ◽  
Complete Information ◽  
Upper Body ◽  
Human Model ◽  
Singular Surfaces ◽  
Rank Deficiency ◽  
Digital Human Model ◽  
Digital Human

This paper presents an applicable formula for determining the workspace of digital human lower extremities. The digital human model has over 100 degrees of freedom (DOF): 94 in the upper body, 14 in the lower extremities, 5 in the neck, 4 in the eyes, and 25 for each hand. The Jacobian row rank deficiency criteria are implemented to determine the singular surfaces that finally form the workspace. The use of this digital human model for determining workspace offers several advantages over direct measurement: (1) the workspace can be visualized in real-time based on offline computation, (2) the workspace can be used for the ergonomic design of products in the virtual prototyping stage, and (3) the calculated workspace includes complete information about the envelope and inside characteristics.

The Iowa Interactive Digital-Human Virtual Environment

2004 ◽  
Author(s):  
Jingzhou Yang ◽  
Karim Abdel-Malek ◽  
Kim Farrell ◽  
Kyle Nebel
Keyword(s):  
Virtual Environment ◽  
Degrees Of Freedom ◽  
Human Model ◽  
Cost Functions ◽  
Objective Functions ◽  
Multi Objective ◽  
Cad System ◽  
Time Simulation ◽  
Digital Humans ◽  
Digital Human

Proper assessment of human reach posture is one of the essential functions for workspace design and evaluation in a CAD system with a built-in human model. Most existing models have used heuristic methods, which provide only the range of feasible human reaching postures, which may or may not include naturalistic reach posture. We present a multi-objective-optimization (MOO)-based approach for predicting realistic reach postures of digital humans, one based on our belief that humans assume different reach postures depending on different cost functions, i.e., multi-objective functions. In this work, the number of degrees of freedom (DOF) associated with the model is unlimited, and ranges of motion of joints are considered. The problem is formulated as MOO and single-objective optimization (SOO) algorithms where one or all cost functions (joint displacement, energy, effort, etc.) are considered as objective functions that drive the model to a solution set. A real-time simulation of the digital human’s motion is applied in the IOWA digital-human virtual environment.

Determining the Static Joint Torques of a Digital Human Model Considering Balance

2009 ◽  
Author(s):  
Jingzhou James Yang ◽  
Yujiang Xiang ◽  
Joo Kim
Keyword(s):  
Human Model ◽  
Joint Torques ◽  
Digital Human Model ◽  
Human Models ◽  
Support Reaction ◽  
Reaction Forces ◽  
Zero Moment ◽  
The Stability ◽  
Physics Based Simulation ◽  
Digital Human

This paper presents a methodology for determining the static joint torques of a digital human model considering balance for both standing and seating tasks. An alternative and efficient formulation of the Zero-Moment Point (ZMP) for static balance and the approximated (ground/seat) support reaction forces/moments are derived from the resultant reaction loads, which includes the gravity and externally applied loads. The proposed method can be used for both standing and seating tasks for assessing the stability/balance of the posture. The proposed formulation can be beneficial to physics-based simulation of humanoids and human models. Also, the calculated joint torques can be considered as an indicator to assess the risks of injuries when human models perform various tasks.

Optimization-based posture prediction for human upper body

Robotica ◽  
2009 ◽  
Vol 27 (4) ◽  
pp. 607-620 ◽  
Author(s):  
Zan Mi ◽  
Jingzhou (James) Yang ◽  
Karim Abdel-Malek
Keyword(s):  
Performance Measures ◽  
Degrees Of Freedom ◽  
Human Performance ◽  
Computational Algorithm ◽  
Performance Measure ◽  
Upper Body ◽  
Cost Functions ◽  
Posture Prediction ◽  
Joint Limits ◽  
Digital Human

SUMMARYA general methodology and associated computational algorithm for predicting postures of the digital human upper body is presented. The basic plot for this effort is an optimization-based approach, where we believe that different human performance measures govern different tasks. The underlying problem is characterized by the calculation (or prediction) of the human performance measure in such a way as to accomplish a specified task. In this work, we have not limited the number of degrees of freedom associated with the model. Each task has been defined by a number of human performance measures that are mathematically represented by cost functions that evaluate to a real number. Cost functions are then optimized, i.e., minimized or maximized, subject to a number of constraints, including joint limits. The formulation is demonstrated and validated. We present this computational formulation as a broadly applicable algorithm for predicting postures using one or more human performance measures.

Degrees of freedom coupling adapted to the upper limb of a digital human model

2017 ◽  
Vol 5 (4) ◽  
pp. 314
Author(s):  
Pierre Olivier Lemieux ◽  
Arnaud Barré ◽  
Nicola Hagemeister ◽  
Rachid Aissaoui
Keyword(s):  
Upper Limb ◽  
Degrees Of Freedom ◽  
Human Model ◽  
Digital Human Model ◽  
Digital Human

Lifting Posture Analysis in Material Handling Using Virtual Humans

2005 ◽  
Author(s):  
Joo H. Kim ◽  
Karim Abdel-Malek ◽  
Jingzhou Yang ◽  
Timothy Marler ◽  
Kyle Nebel
Keyword(s):  
Material Handling ◽  
Equations Of Motion ◽  
Prediction Method ◽  
Metabolic Energy ◽  
Joint Torque ◽  
Human Model ◽  
Risk Level ◽  
Posture Analysis ◽  
Joint Torques ◽  
Digital Human

Adopting appropriate postures during manual material-handling tasks is the key to reducing human joint injuries. Although much experimentation has been conducted in an effort to model lifting, such an approach is not general enough to consider all potential scenarios in material handling. Thus, in this paper an optimization-based motion prediction method is used to simulate realistic lifting postures and predict joint torques to evaluate the risk level of injury. A kinematically realistic digital human model has been developed such that the complicated musculoskeletal human structure is modeled as a combination of serial chains using the generalized coordinates. Lagrange’s equations of motion and metabolic energy rate are derived for the digital human. The proposed method has been implemented to predict and evaluate the lifting postures based on the metabolic rate and joint torques. Our results show that different amount of external loads and tasks lead to different human postures and joint torque distribution, thus different risk level of injury.

3D HUMAN LIFTING MOTION PREDICTION WITH DIFFERENT PERFORMANCE MEASURES

2012 ◽  
Vol 09 (02) ◽  
pp. 1250012 ◽  
Author(s):  
YUJIANG XIANG ◽  
JASBIR S. ARORA ◽  
KARIM ABDEL-MALEK
Keyword(s):  
Performance Measures ◽  
Shear Force ◽  
Degrees Of Freedom ◽  
Human Performance ◽  
Three Dimensional ◽  
Optimal Solution ◽  
Performance Measure ◽  
Maximum Pressure ◽  
Pressure Force ◽  
Digital Human

This paper presents an optimization-based method for predicting a human dynamic lifting task. The three-dimensional digital human skeletal model has 55 degrees of freedom. Lifting motion is generated by minimizing an objective function (human performance measure) subjected to basic physical and kinematical constraints. Four objective functions are investigated in the formulation: the dynamic effort, the balance criterion, the maximum shear force at spine joint and the maximum pressure force at spine joint. The simulation results show that various human performance measures predict different lifting strategies: the balance and shear force performance measures predict back-lifting motion and the dynamic effort and pressure force performance measures generate squat-lifting motion. In addition, the effects of box locations on the lifting strategies are also studied. All kinematics and kinetic data are successfully predicted for the lifting motion by using the predictive dynamics algorithm and the optimal solution was obtained in about one minute.

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