An inverse optimization approach for determining weights of joint displacement objective function for upper body kinematic posture prediction

Robotica ◽  
2011 ◽  
Vol 30 (3) ◽  
pp. 389-404 ◽  
Author(s):  
Qiuling Zou ◽  
Qinghong Zhang ◽  
Jingzhou (James) Yang ◽  
Jared Gragg
Keyword(s):  
Objective Function ◽  
Optimization Problem ◽  
Inverse Optimization ◽  
Displacement Function ◽  
Upper Body ◽  
Optimization Approach ◽  
Joint Angles ◽  
Design Variables ◽  
Posture Prediction ◽  
Joint Displacement

SUMMARYHuman posture prediction can often be formulated as a nonlinear multiobjective optimization (MOO) problem. The joint displacement function is considered as a benchmark of human performance measures. When the joint displacement function is used as the objective function, posture prediction is a MOO problem. The weighted-sum method is commonly used to find a Pareto solution of this MOO problem. Within the joint displacement function, the relative value of the weights associated with each joint represents the relative importance of that joint. Usually, weights are determined by trial and error approaches. This paper presents a systematic approach via an inverse optimization approach to determine the weights for the joint displacement function in posture prediction. This inverse optimization problem can be formulated as a bi-level optimization problem. The design variables are joint angles and weights. The cost function is the summation of the differences between two set of joint angles (the design variables and the realistic posture). Constraints include (1) normalized weights within limits and (2) an inner optimization problem to solve for joint angles (predicted posture). Additional constraints such as weight limits and weight linear equality constraints, obtained through observations, are also implemented in the formulation to test the method. A 24 degree of freedom human upper body model is used to study the formulation and visualize the prediction. An in-house motion capture system is used to obtain the realistic posture. Four different percentiles of subjects are selected to run the experiment. The set of weights for the general seated posture prediction is obtained by averaging all weights for all subjects and all tasks. On the basis of obtained set of weights, the predicted postures match the experimental results well.

Shape Optimization of Hydraulic Structures: an Example of an Optimum Design of a Fish Passage

10.29007/2k64 ◽  
2018 ◽  
Author(s):  
Pat Prodanovic ◽  
Cedric Goeury ◽  
Fabrice Zaoui ◽  
Riadh Ata ◽  
Jacques Fontaine ◽  
...  
Keyword(s):  
Numerical Model ◽  
Shape Optimization ◽  
Objective Function ◽  
Optimum Design ◽  
Optimization Problem ◽  
A Priori ◽  
Coupled System ◽  
Fish Passage ◽  
Hydraulic Structures ◽  
Design Variables

This paper presents a practical methodology developed for shape optimization studies of hydraulic structures using environmental numerical modelling codes. The methodology starts by defining the optimization problem and identifying relevant problem constraints. Design variables in shape optimization studies are configuration of structures (such as length or spacing of groins, orientation and layout of breakwaters, etc.) whose optimal orientation is not known a priori. The optimization problem is solved numerically by coupling an optimization algorithm to a numerical model. The coupled system is able to define, test and evaluate a multitude of new shapes, which are internally generated and then simulated using a numerical model. The developed methodology is tested using an example of an optimum design of a fish passage, where the design variables are the length and the position of slots. In this paper an objective function is defined where a target is specified and the numerical optimizer is asked to retrieve the target solution. Such a definition of the objective function is used to validate the developed tool chain. This work uses the numerical model TELEMAC- 2Dfrom the TELEMAC-MASCARET suite of numerical solvers for the solution of shallow water equations, coupled with various numerical optimization algorithms available in the literature.

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.

Frequency optimization of laminated functionally graded carbon nanotube reinforced composite quadrilateral plates using smoothed FEM and evolution algorithm

2017 ◽  
Vol 52 (14) ◽  
pp. 1971-1986 ◽  
Author(s):  
T Vo-Duy ◽  
T Truong-Thi ◽  
V Ho-Huu ◽  
T Nguyen-Thoi
Keyword(s):  
Carbon Nanotube ◽  
Optimization Problem ◽  
Volume Fraction ◽  
Differential Evolution Algorithm ◽  
Composite Plates ◽  
Functionally Graded ◽  
Optimization Approach ◽  
Reinforced Composite ◽  
Design Variables ◽  
Evolution Algorithm

The paper presents an efficient numerical optimization approach to deal with the optimization problem for maximizing the fundamental frequency of laminated functionally graded carbon nanotube-reinforced composite quadrilateral plates. The proposed approach is a combination of the cell-based smoothed discrete shear gap method (CS-DSG3) for analyzing the first natural frequency of the functionally graded carbon nanotube reinforced composite plates and a global optimization algorithm, namely adaptive elitist differential evolution algorithm (aeDE), for solving the optimization problem. The design variables are the carbon nanotube orientation in the layers and constrained in the range of integer numbers belonging to [−900 900]. Several numerical examples are presented to investigate optimum design of quadrilateral laminated functionally graded carbon nanotube reinforced composite plates with various parameters such as carbon nanotube distribution, carbon nanotube volume fraction, boundary condition and number of layers.

Nonlinear inverse optimization approach for determining the weights of objective function in standing reach tasks

2012 ◽  
Vol 63 (4) ◽  
pp. 791-801
Author(s):  
Qiuling Zou ◽  
Qinghong Zhang ◽  
Jingzhou (James) Yang ◽  
Aimee Cloutier ◽  
Esteban Pena-Pitarch
Keyword(s):  
Objective Function ◽  
Inverse Optimization ◽  
Optimization Approach

Runner Optimization for In-Mold Assembly of Multi-Material Compliant Mechanisms

2011 ◽  
Author(s):  
Wojciech Bejgerowski ◽  
Satyandra K. Gupta
Keyword(s):  
Optimization Problem ◽  
Compliant Mechanisms ◽  
Compliant Mechanism ◽  
Polymer Melt ◽  
Injection Molding Process ◽  
Optimization Approach ◽  
Assembly Process ◽  
Molding Process ◽  
Design Variables

The runner system in injection molding process is used to supply the polymer melt from injection nozzle to the gates of final part cavities. Realizing complex multi-material mechanisms by in-mold assembly process requires special runner layout design considerations due to the existence of the first stage components. This paper presents the development of an optimization approach for runner systems in the in-mold assembly of multi-material compliant mechanisms. First, the issues specific to the in-mold assembly process are identified and analyzed. Second, the general optimization problem is formulated by identification of all parameters, design variables, objective functions and constraints. Third, the implementation of the optimization problem in Matlab® environment is described based on a case study of a runner system for an in-mold assembly of a MAV drive mechanism. This multi-material compliant mechanism consists of seven rigid links interconnected by six compliant hinges. Finally, several optimization approaches are analyzed to study their performance in solving the formulated problem. The most appropriate optimization approach is selected. The case study showed the applicability of the developed optimization approach to runner systems for complex in-mold assembled multi-material mechanism designs.

Effect of Uncertainty on Human Posture Prediction

2014 ◽  
Author(s):  
Ning Li ◽  
James Yang
Keyword(s):  
Center Of Mass ◽  
Interaction Force ◽  
Upper Body ◽  
Random Parameters ◽  
Link Length ◽  
Deterministic Optimization ◽  
Reliability Based Design ◽  
Design Variables ◽  
Posture Prediction ◽  
Digital Human

Posture prediction is a key component in digital human modeling and simulation. Deterministic optimization-based posture prediction formulations have been proposed. However, there exist uncertainties in human anthropometric (human height, link length, center of mass of segments, and moment of inertia, etc.) and environment parameters (location, interaction force), which affects the predicted posture. This paper attempts to study the effect of uncertainty on predicted posture. The single-loop reliability based design optimization (RBDO) method is adapted to predict posture under uncertainties. All random parameters are assumed to have normal distribution. A 24-degree of freedom (DOF) upper body model is used. In this pilot study, it is assumed that one link length and one joint angle are random parameters. The other design variables and parameters are deterministic. With the empirical rule, three cases are investigated for posture prediction. SNOPT software solver is employed to solve the optimization problem. Through comparison with deterministic optimization result and experimental data, the predicted postures from RBDO simulation show that the reliability index affects the predicted posture to some extent.

A Computer-Aided Optimization Approach for the Design of Injection Mold Cooling Systems

1998 ◽  
Vol 120 (2) ◽  
pp. 165-174 ◽  
Author(s):  
L. Q. Tang ◽  
K. Pochiraju ◽  
C. Chassapis ◽  
S. Manoochehri
Keyword(s):  
Finite Element ◽  
Optimal Design ◽  
Constrained Optimization ◽  
Objective Function ◽  
Optimization Problem ◽  
Temperature Gradients ◽  
Optimization Approach ◽  
Injection Mold ◽  
Constrained Optimization Problem ◽  
Cooling Systems

A methodology is presented for the design of optimal cooling systems for injection mold tooling which models the mold cooling as a nonlinear constrained optimization problem. The design constraints and objective function are evaluated using Finite Element Analysis (FEA). The objective function for the constrained optimization problem is stated as minimization of both a function related to part average temperature and temperature gradients throughout the polymeric part. The goal of this minimization problem is to achieve reduction of undesired defects as sink marks, differential shrinkage, thermal residual stress built-up, and part warpage primarily due to non-uniform temperature distribution in the part. The cooling channel size, locations, and coolant flow rate are chosen as the design variables. The constrained optimal design problem is solved using Powell’s conjugate direction method using penalty function. The cooling cycle time and temperature gradients are evaluated using transient heat conduction simulation. A matrix-free algorithm of the Galerkin Finite Element Method (FEM) with the Jacobi Conjugate Gradient (JCG) scheme is utilized to perform the cooling simulation. The optimal design methodology is illustrated using a case study.

scholarly journals Static Balancing of Robot Mechanisms and Manipulation Devices

2018 ◽  
Vol 68 (2) ◽  
pp. 77-90
Author(s):  
Stefan Segla
Keyword(s):  
Objective Function ◽  
Multibody Dynamics ◽  
Optimization Problem ◽  
Energy Savings ◽  
Driving Forces ◽  
Optimal Designs ◽  
Constant Force ◽  
Static Balancing ◽  
Design Variables ◽  
Gravity Load

AbstractThe paper deals with static balancing of various kinds of mechanisms and manipulation devices using spring balancing mechanisms. In case of parallelogram robots and manipulation mechanisms a spring balancing mechanism exerting a constant force is used. Problems of static balancing of variable payloads are also presented and investigated in the paper. Static balancing is formulated as an optimization problem with the objective function expressing minimization of the forces acting in the driving joints. As design variables geometrical variables and spring stiffnesses and their unloaded lengths are used. Optimization Toolbox for Use with Matlab and GOOD (Generator Of Optimal Designs) are used to solve the static balancing problems. The optimized mechanisms are evaluated by using multibody dynamics programs taking into account friction effects in mechanism joints. The results of static balancing optimization show essential reduction of the gravity load in drive joints and consequently driving forces with important energy savings.

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