Prediction of initial and final postures for motion planning in human manual manipulation tasks based on cognitive decision making

James Yang, Brad Howard

Research output: Contribution to journalArticlepeer-review

Abstract

Humans are daily presented with tasks that they complete with little effort or even consideration of the planning that goes into the movement. Movements such as manual manipulation tasks are completed with ease, even though the complexities and years of learned behavior are largely hidden from the person. Digital human modeling (DHM) and specifically optimization-based posture and motion prediction methodologies have employed numerical methods in order to simulate/predict/analyze human movements. However, these movements are heavily constrained such that the planning of the motion/posture is explicitly provided in the formulation of the problem. This paper presents the addition of cognitive principles into the optimization-based posture and motion prediction formulations. The simulation/prediction of manual manipulation tasks is considered such that a single formulation can accomplish multiple tasks. It adopts a theory from cognitive psychology referred to as the end-state comfort effect in order to derive general constraints for the prediction of the initial and final posture states that frame the movement related to the manual manipulation task. It considers multiple tasks from the literature that have been heavily studied through experimentation in order to evaluate the efficacy of the formulation. The results show strong correlation with observations reported in the literature.

Original languageEnglish
Article number011007-1
JournalJournal of Computing and Information Science in Engineering
Volume20
Issue number1
DOIs
StatePublished - Feb 2020

Keywords

  • Cognitive theories
  • Computer-aided design
  • Digital human modeling
  • End-state comfort effect
  • Human computer interfaces/interactions
  • Model-based systems engineering
  • Terminal state

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