Modeling the Effect of Force Feedback for 3D Steering Tasks

Abstract

Path steering is an interaction task of how quickly one may navigate through a path. The steering law, proposed by Accot and Zhai [AZ97], is a predictive model which describes the time to accomplish a 2D steering task as a function of the path length and width. In this paper, we study a 3D steering task in the presence of force feedback. Our goal is to extend the application of the steering law in such a task and find out, if possible, additional predictors for users' temporal performance. In particular, we quantitatively examine how the amount of force feedback influences the movement time. We have carried out a repeated-measures-design experiment with varying path length, width and force magni- tude. The results indicate that the movement time can be successfully modeled by path length, width and force magnitude. The relationship evidences that the efficiency of the tasks can be improved once an appropriate force magnitude is applied. Additionally, we have compared the capacity of our model to the steering law. According to Akaike Information Criterion (AIC), our model provides a better description for the movement time when the force magnitude can vary. The new model can be utilized as a guideline for designing the experiments with a haptic device.