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An ergonomics virtual human is built, which is a unified framework made up of biomechanics/physiology-based model, anthropometrical model, posture and motion model, task model, human reactions and decision-making model and human factor analysis model.
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A simple and effective motion model for this particular task is the approximation of the predicted workspace occupancy of the human via a cylinder that encompasses the worker's arm as he or she completes the placing task, as this is the only part of the human the robot can reach.
Therefore, in the prediction task, the motion model must be applied with a randomization to reflect the system random error and the sensor noise (Monte Carlo localization) [13].
The main steps of the algorithm are described below: Prediction task propagates the current state of particles in the filter using motion model (2).
A multi-robot mapping and exploration task is utilised as a model task to evaluate the task allocation process.
(d) Learnt motion model for the bending action.
The last three parameters describe a helical motion model, where periodic motion is reliably established.
The Brownian motion model differs in several respects.
Microsatellite analyses were performed using the Brownian motion model.
Otherwise, the motion model would be too complex.
The models are applied to human performance in a motion discrimination task that induces perceptual misjudgements of a target direction of motion by task irrelevant motion in the spatial surround of the target stimulus (motion repulsion).
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