Determining weights of joint displacement objective function for standing reach tasks
Visualitza/Obre
Ponència (401,6Kb) (Accés restringit)
Sol·licita una còpia a l'autor
Què és aquest botó?
Aquest botó permet demanar una còpia d'un document restringit a l'autor. Es mostra quan:
- Disposem del correu electrònic de l'autor
- El document té una mida inferior a 20 Mb
- Es tracta d'un document d'accés restringit per decisió de l'autor o d'un document d'accés restringit per política de l'editorial que té aplicat un embargament superior a 6 mesos i està vinculat a un projecte finançat per la Comissió Europea
Tipus de documentText en actes de congrés
Data publicació2011
Condicions d'accésAccés restringit per decisió de l'autor
Abstract
This paper presents an inverse optimization approach to determine the weights for the joint displacement function in
standing reach tasks. 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 sets
of joint angles (the design variables and the realistic standing reach posture). Constraints include (1) normalized
weights within limits; (2) an inner optimization problem to solve for joint angles (predicted standing reach posture).
Additional constraints such as weight linear equality constraints, obtained through observations, are also
implemented in the formulation to test the method. A 52 degree-of-freedom (DOF) human whole body model is
used to study the formulation and visualize the prediction. An in-house motion capture system is used to obtain the
realistic standing reach posture. Total 12 subjects (three subjects for each percentiles in stature of 5th percentile
female, 50th percentile female, 50th percentile male and 95th percentile male) are selected to run the experiment. The
set of weights for the general standing reach tasks is obtained by averaging all weights for all subjects and all tasks.
Based on obtained set of weights, the predicted standing reach postures have good correlation with the experimental
results. The presented formulation can be used to determine the weights of cost function within any multi-objective
optimization (MOO) problems such as any types of posture prediction and motion prediction.
CitacióZou, Q. [et al.]. Determining weights of joint displacement objective function for standing reach tasks. A: International Symposium on Digital Human Modeling. "First International Symposium on Digital Human Modeling". Lyon: 2011, p. 1-7.
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
2160Peña.pdf![]() | Ponència | 401,6Kb | Accés restringit |