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.

Physics-Based Seated Posture Prediction for Pregnant Women and Validation Considering Ground and Seat Pan Contacts

2012 ◽  
Vol 134 (7) ◽  
Author(s):  
Bradley Howard ◽  
Aimee Cloutier ◽  
Jingzhou (James) Yang
Keyword(s):  
Pregnant Women ◽  
Objective Function ◽  
Linear Regression Analysis ◽  
Joint Torque ◽  
Joint Torques ◽  
Design Variables ◽  
Optimization Formulation ◽  
Posture Prediction ◽  
Seated Posture ◽  
End Effectors

An understanding of human seated posture is important across many fields of scientific research. Certain demographics, such as pregnant women, have special postural limitations that need to be considered. Physics-based posture prediction is a tool in which seated postures can be quickly and thoroughly analyzed, as long the predicted postures are realistic. This paper proposes and validates an optimization formulation to predict seated posture for pregnant women considering ground and seat pan contacts. For the optimization formulation, the design variables are joint angles (posture); the cost function is dependent on joint torques. Constraints include joint limits, joint torque limits, the distances from the end-effectors to target points, and self-collision avoidance constraints. Three different joint torque cost functions have been investigated to account for the special postural characteristics of pregnant women and consider the support reaction forces (SRFs) associated with seated posture. Postures are predicted for three different reaching tasks in common reaching directions using each of the objective function formulations. The predicted postures are validated against experimental postures obtained using motion capture. A linear regression analysis was used to evaluate the validity of the predicted postures and was the criteria for comparison between the different objective functions. A 56 degree of freedom model was used for the posture prediction. Use of the objective function minimizing the maximum normalized joint torque provided an R2 value of 0.828, proving superior to either of two alternative functions.

Design Human-Robot Collaborative Lifting Task Using Optimization

2021 ◽  
Author(s):  
Asif Arefeen ◽  
Yujiang Xiang
Keyword(s):  
Degrees Of Freedom ◽  
Joint Angle ◽  
Joint Torque ◽  
Robotic Arm ◽  
Inverse Dynamic ◽  
Floating Base ◽  
Grasping Forces ◽  
Design Variables ◽  
Human Arm ◽  
Lifting Task

Abstract In this paper, an optimization-based dynamic modeling method is used for human-robot lifting motion prediction. The three-dimensional (3D) human arm model has 13 degrees of freedom (DOFs) and the 3D robotic arm (Sawyer robotic arm) has 10 DOFs. The human arm and robotic arm are built in Denavit-Hartenberg (DH) representation. In addition, the 3D box is modeled as a floating-base rigid body with 6 global DOFs. The interactions between human arm and box, and robot and box are modeled as a set of grasping forces which are treated as unknowns (design variables) in the optimization formulation. The inverse dynamic optimization is used to simulate the lifting motion where the summation of joint torque squares of human arm is minimized subjected to physical and task constraints. The design variables are control points of cubic B-splines of joint angle profiles of the human arm, robotic arm, and box, and the box grasping forces at each time point. A numerical example is simulated for huma-robot lifting with a 10 Kg box. The human and robotic arms’ joint angle, joint torque, and grasping force profiles are reported. These optimal outputs can be used as references to control the human-robot collaborative lifting task.

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.

scholarly journals Lower Extremity Motor Impairments in Ambulatory Chronic Hemiparetic Stroke: Evidence for Lower Extremity Weakness and Abnormal Muscle and Joint Torque Coupling Patterns

2017 ◽  
Vol 31 (9) ◽  
pp. 814-826 ◽  
Author(s):  
Natalia Sánchez ◽  
Ana Maria Acosta ◽  
Roberto Lopez-Rosado ◽  
Arno H. A. Stienen ◽  
Julius P. A. Dewald
Keyword(s):  
Lower Extremity ◽  
Degrees Of Freedom ◽  
Joint Torque ◽  
Motor Impairments ◽  
Lower Extremity Weakness ◽  
Joint Torques ◽  
Hemiparetic Stroke ◽  
Chronic Hemiparetic Stroke ◽  
Hip Extension ◽  
Flexion And Extension

Although global movement abnormalities in the lower extremity poststroke have been studied, the expression of specific motor impairments such as weakness and abnormal muscle and joint torque coupling patterns have received less attention. We characterized changes in strength, muscle coactivation and associated joint torque couples in the paretic and nonparetic extremity of 15 participants with chronic poststroke hemiparesis (age 59.6 ± 15.2 years) compared with 8 age-matched controls. Participants performed isometric maximum torques in hip abduction, adduction, flexion and extension, knee flexion and extension, ankle dorsi- and plantarflexion and submaximal torques in hip extension and ankle plantarflexion. Surface electromyograms (EMGs) of 10 lower extremity muscles were measured. Relative weakness (paretic extremity compared with the nonparetic extremity) was measured in poststroke participants. Differences in EMGs and joint torques associated with maximum voluntary torques were tested using linear mixed effects models. Results indicate significant poststroke torque weakness in all degrees of freedom except hip extension and adduction, adductor coactivation during extensor tasks, in addition to synergistic muscle coactivation patterns. This was more pronounced in the paretic extremity compared with the nonparetic extremity and with controls. Results also indicated significant interjoint torque couples during maximum and submaximal hip extension in both extremities of poststroke participants and in controls only during maximal hip extension. Additionally, significant interjoint torque couples were identified only in the paretic extremity during ankle plantarflexion. A better understanding of these motor impairments is expected to lead to more effective interventions for poststroke gait and posture.

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.

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.

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.

Optimization-Based Seated Posture Prediction Considering Contact With Environment

2011 ◽  
Author(s):  
Brad Howard ◽  
Jingzhou James Yang
Keyword(s):  
Center Of Pressure ◽  
Optimization Techniques ◽  
The Body ◽  
Human Model ◽  
Joint Torques ◽  
Pressure Mapping ◽  
Support Reaction ◽  
Posture Prediction ◽  
Reaction Forces ◽  
Recursive Dynamics

People can spend much of everyday completing seated tasks. Therefore it is important to understand postures needed to complete seated tasks, and the associated environmental contacts. This paper presents a method to predict seated postures and the general forces needed in order to support resulting postural configurations. This study uses optimization techniques to predict human posture based on a 56 degree of freedom (DOF) 50th percentile female human model. The support reaction forces (SRFs) are predicted using joint torques and the zero-moment point (ZMP) formulation derived from the Lagrangian recursive dynamics. The SRFs are applied at points on the body based on center of pressure (COP) locations gathered from pressure mapping experiments. The specific application points include the two feet, the two thighs, and back. Multiple seated orientations based on an experimental study found in published literature are simulated. When comparing these simulation results to the literature data, a good correlation can be established, which provides an initial validation of the proposed methods.

Kinematic and Kinetic Constraints on Arm, Trunk, and Leg Segments in Target-Reaching Movements

2005 ◽  
Vol 93 (1) ◽  
pp. 352-364 ◽  
Author(s):  
James S. Thomas ◽  
Daniel M. Corcos ◽  
Ziaul Hasan
Keyword(s):  
Degrees Of Freedom ◽  
Neural Control ◽  
Time Course ◽  
Sagittal Plane ◽  
Principal Component ◽  
Joint Torque ◽  
Trunk Flexion ◽  
Joint Torques ◽  
Joint Task ◽  
Task Conditions

We studied target reaching tasks involving not only the arms but also the trunk and legs, which necessitated some trunk flexion. Such tasks can be successfully completed using an infinite number of combinations of segment motions due to the inherent kinematic redundancy with the excessive degrees of freedom (DOFs). Sagittal plane motions of six segments (shank, thigh, pelvis, trunk, humerus, and forearm) and dynamic torques of six joints (ankle, knee, hip, lumbar, shoulder, and elbow) were analyzed separately by principal component (PC) analyses to determine if there was a commonality among the shapes of the respective waveforms. Additionally, PC analyses were used to probe for constraining relationships among the 1) relative magnitudes of segment excursions and 2) the peak-to-peak dynamic joint torques. In summary, at the kinematic level, the tasks are simplified by the use of a single common waveform for all segment excursions with 89.9% variance accounted for (VAF), but with less fixed relationships among the relative scaling of the magnitude of segment excursions (62.2% VAF). However, at the kinetic level, the time course of the dynamic joint torques are not well captured by a single waveform (72.7% VAF), but the tasks are simplified by relatively fixed relationships among the scaling of dynamic joint torque magnitudes across task conditions (94.7% VAF). Taken together, these results indicate that, while the effective DOFs in a multi-joint task are reduced differently at the kinematic and kinetic levels, they both contribute to simplifying the neural control of these tasks.

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