Optimal Posture and Supporting Hand Force Prediction for Common Automotive Assembly One-Handed Tasks

2014 ◽  
Vol 6 (2) ◽  
Author(s):  
Bradley Howard ◽  
James Yang ◽  
Burak Ozsoy
Keyword(s):  
Stability Analysis ◽  
Degrees Of Freedom ◽  
Human Performance ◽  
Performance Measure ◽  
Joint Torque ◽  
External Support ◽  
Human Model ◽  
Automotive Assembly ◽  
External Forces ◽  
Hand Forces

People often complete tasks using one hand for the task and one hand for support. These one-handed support tasks can be found in many different types of jobs, such as automotive assembly jobs. Optimization-based posture prediction has proven to be a valid tool in predicting the postures necessary to complete the tasks, but the related external support forces have been prescribed and not predicted. This paper presents a method in which the optimal posture and related supporting hand forces can be predicted simultaneously using optimization and stability analysis techniques. Postures are evaluated using a physics-based human performance measure (HPM) while external forces are assessed using stability analysis. The physics-based performance measures are based on joint torque. Stability is analyzed using criteria based on a 3D zero moment point (ZMP). The human model used in the prediction contains 56 degrees of freedom and is based on a 50th percentile female in stature. Tasks based on common automotive assembly one-handed tasks found in literature are considered as examples to test the proposed method. Overall, the predicted supporting hand forces have good correlation with experimentally measured forces.

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.

Prediction of Supporting Hand Forces for Common Automotive Assembly Tasks Based on Optimization and Stability Techniques for Given Posture

2012 ◽  
Author(s):  
Bradley Howard ◽  
Jingzhou (James) Yang ◽  
Guolai Yang
Keyword(s):  
Three Dimensional ◽  
Joint Torque ◽  
Predictive Tool ◽  
Work Tasks ◽  
Automotive Assembly ◽  
Zero Moment ◽  
External Forces ◽  
Electrical Components ◽  
Assembly Tasks ◽  
Hand Forces

Quite often people are faced with one handed tasks in which the other hand is needed for support. Without these supporting external forces, postures may be unstable, rendering the task impossible. Automotive assembly line operators are confronted with these types of tasks every day, such as hose installations and the connection of electrical components. Determining the optimal location and forces for the supporting hand is important to minimize potential injuries of operators. Traditionally, these supporting hand forces are measured by experiments. This work attempts to provide an important predictive tool that promises to be of considerable value to companies in predicting leaning forces in work simulation for the proactive ergonomic assessment of work tasks. It presents a method using optimization and stability analysis techniques. Stability is based on the calculation of a three dimensional zero moment point (3D-ZMP) and the resultant reaction loads, calculated from the joint torque. The formulation of the optimization problem used to predict the supporting hand forces is presented and tested using tasks commonly encountered by automotive assembly workers. The results are compared to that in literature, providing an initial validation of the methods. The predicted external forces fell within the 95% confidence intervals calculated from the literature for all 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.

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.

A NEW STABILITY CRITERION FOR HUMAN SEATED TASKS WITH GIVEN POSTURES

2012 ◽  
Vol 09 (03) ◽  
pp. 1250015 ◽  
Author(s):  
BRADLEY HOWARD ◽  
JINGZHOU YANG
Keyword(s):  
Stability Analysis ◽  
Stability Criterion ◽  
Center Of Mass ◽  
Reaction Force ◽  
Joint Torque ◽  
Human Model ◽  
Digital Human Model ◽  
Applied Forces ◽  
The Stability ◽  
Digital Human

In digital human modeling (DHM), the analysis of postural stability has five main goals: to determine if a posture is stable or unstable through an explicit criterion; to quantify the level of stability or provide a margin of stability that accounts for the height of the center of mass (COM) above the support plane(s); to be valid in the presence of externally applied forces and moments; be able to assess stability when multiple noncoplanar support planes exist, as is the case with seated postures; and to give insight into the support reaction force (SRF) distribution. To date, there is not a method for analyzing stability that can effectively meet each goal. This paper presents a new stability criterion and stability analysis that accomplishes each intended goal. The stability analysis is derived from the calculation of joint torque using the recursive Lagrangian dynamic formulation. A 56-degree-of-freedom (DOF) articulated digital human model is used to model seated postures to demonstrate the proposed stability criterion. Different given postures with different external load cases are presented.

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.

Predictive Simulation of Human Ladder Climbing

2013 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Yujiang Xiang ◽  
Mahdiar Hariri ◽  
Rajan Bhatt ◽  
Jasbir S. Arora ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Motion Tracking ◽  
Mechanical Energy ◽  
Joint Torque ◽  
Human Model ◽  
Joint Torques ◽  
Contact Points ◽  
Design Variables ◽  
Reaction Forces ◽  
Hands And Feet

An optimization formulation for human ladder climbing simulation is presented. The human model has 55 degrees of freedom — 49 revolute joints and 6 global translation & rotation joints. It is assumed that the ladder climbing motion is symmetric and periodic. The formulation starts with four contact points with both hands and feet. Then, hand and foot moves up and it ends with four contact points again. Design variables are the joint angle profiles and contact reaction forces. The objective function is combined with dynamic efforts and motion tracking. The dynamic efforts are joint torque square which is proportional to the mechanical energy. The motion tracking is the motion capture data tracking so that the motion follows the natural ladder climb motion as well. The dynamics results with joint torques and reaction forces are recovered and analyzed from the simulation.

Optimization-based dynamic 3D human running prediction: effects of foot location and orientation

Robotica ◽  
2014 ◽  
Vol 33 (2) ◽  
pp. 413-435 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Yujiang Xiang ◽  
Jasbir S. Arora ◽  
Karim Abdel-Malek
Keyword(s):  
Human Subjects ◽  
Reaction Force ◽  
Three Dimensional ◽  
Performance Measure ◽  
Joint Torque ◽  
Upper Body ◽  
Human Model ◽  
Curved Paths ◽  
Dynamics Method ◽  
Human Running

SUMMARYThis paper presents optimization-based dynamic three-dimensional (3D) human running prediction. A predictive dynamics method is used to formulate the running problem, and normal running is formulated as a symmetric and cyclic motion. In addition, a slow jog along curved paths has been formulated. It is a non-symmetric running motion, so a stride formulation has been used. 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 effects of foot location and orientation on the running motion prediction are simulated and studied. Simulation results from this methodology show good correlation with experimental data obtained from human subjects.

Development of 3D Equipment Interaction With Predictive Dynamics in Human Motion Simulation

2016 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Yujiang Xiang
Keyword(s):  
Human Body ◽  
Degrees Of Freedom ◽  
Reaction Force ◽  
Human Motion ◽  
The Body ◽  
Joint Torque ◽  
Human Model ◽  
Motion Simulation ◽  
Predictive Dynamics ◽  
Human Motion Simulation

3D equipment interaction module in human motion simulation is developed in this paper. A predictive dynamics method is used to simulate human motion, and a helmet is modeled as the equipment that is attached to the human body. We then implement this method using the predictive dynamics task of walking. A mass-spring-damper system is attached at the top of the head as a helmet model. The equations of motion for the helmet are also derived in a recursive Lagrangian formulation within the same inertial reference frame as the human model’s. The total number of degrees of freedom for the human model is 55 — 6 degrees of freedom for global translation and rotation, and 49 degrees of freedom for the body. The helmet has 7 degrees of freedom, but 6 of them are dependent to the human model. The movement of the helmet is analyzed due to the human motion. Then, the reaction force between the human body and the equipment is calculated. Once the reaction force is obtained, it is applied to the human body as an external force in the predictive dynamics optimization process. Results include the motion of equipment, the force acting on body at the attachment point, the joint torque profiles, and the ground reaction force profiles at the foot contacting point.

Dynamic Optimization of Human Running With Analytical Gradients

2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Hyun-Joon Chung ◽  
Jasbir S. Arora ◽  
Karim Abdel-Malek ◽  
Yujiang Xiang
Keyword(s):  
Human Subjects ◽  
Reaction Force ◽  
Performance Measure ◽  
Joint Torque ◽  
Upper Body ◽  
Human Model ◽  
Dynamic Prediction ◽  
Foot Strike ◽  
Analytical Gradients ◽  
Human Running

The optimization-based dynamic prediction of 3D human running motion is studied in this paper. A predictive dynamics method is used to formulate the running problem, and normal running is formulated as a symmetric and cyclic motion. Recursive Lagrangian dynamics with analytical gradients for all the constraints and objective function are incorporated in the optimization process. The dynamic effort is used as the performance measure, and the impulse at the foot strike 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 (GRF) is determined. Several cause-and-effect cases are studied, and the formulation for upper-body yawing motion is proposed and simulated. Simulation results from this methodology show good correlation with experimental data obtained from human subjects and the existing literature.

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