Probabilistic sensitivity analysis of in-vehicle reach tasks for digital human models considering anthropometric measurement uncertainty

Aimee Cloutier, Jared Gragg, James Yang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

For design using digital human models, human anthropometry data are required as input and are extracted from measurements. There is inherent error associated with these measurements which impacts the output of the simulation. Current techniques in digital human modeling applications primarily employ deterministic methods which are not well suited for handling variability in anthropometric measurement. An alternative to deterministic methods is probabilistic/sensitivity analysis. This study presents a probabilistic sensitivity approach to gain insights into how uncertainty in anthropometric measurements can affect the results of a digital human model with the specific application of vehicle-related reach tasks. Sensitivity levels are found to determine the importance of variability in each joint angle and link length to the final reach. A55-degree of freedom (DOF) digital human model is introduced to demonstrate the sensitivity approach for reach tasks. Seven right-hand reach target points and two left-hand reach target points (creating a total of 14 reach tasks) within a vehicle are used to compare the sensitivities in the joint angles and link lengths resulting from measurement uncertainty. The results show that the importance of each joint angle or link length is dependent on the characteristics of the reach task and sensitivities for joint angles, and link lengths are different for each reach task.

Original languageEnglish
Pages (from-to)498-512
Number of pages15
JournalRobotica
Volume33
Issue number3
DOIs
StatePublished - Mar 31 2015

Keywords

  • Digital human modeling
  • Posture
  • Reach tasks
  • Sensitivity
  • Uncertainty

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