Misalignment Effect Function for Oblique Rotation of a Teleoperations Viewpoint: Counterintuitive Predictions and Implications for Fitts' Law

Ellis, Stephen R.; Adelstein, Bernard D.; Yeom, Kiwon

doi:10.3182/20130811-5-us-2037.00027

Cited by 1 publication

(5 citation statements)

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“…We now extend our study of the MEF into the temporal domain. This study of temporal phenomena associated with the MEF is assisted in a concrete way by our previous results (Ellis et al, 2013) when we confirmed our somewhat counterintuitive prediction that the disturbance in coordinated movement caused by a display-control rotation should get relatively harder as the distance between the participants' controlled element and their target decreases. In that study, we placed targets at two distances (11 and 22 cm) from an origin centered in front of the participant and used a Fick-gimbal yaw-pitch-roll convention to find a set of controlto-display coordinate rotations.…”

Section: Introductionsupporting

confidence: 84%

“…We have argued in previous papers that users of telerobotic systems need to be able to manage possibly awkwardly rotated views of their worksites in order to monitor automation or provide manual backup , 2013. The consequent need to understand the operational control difficulty imposed by rotation of operators' views has both spatial and temporal aspects.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, these rotations allow the misalignment problem to be presented to participants in a more varied, randomly ordered way that is not conducive to adaptation or learning. Figure 4 displays the MEF reported by Ellis et al (2013) for these generic rotations, collapsing results across pitch and yaw and separates them only by the final roll rotation. This figure confirms an earlier prediction that the shorter targeting movements should be more difficult, as evidenced their larger less efficient nPL.…”

Section: Introductionmentioning

confidence: 99%

“…With the no-rotation case, i.e., Level 0 (0, 0, 0), three levels of rotation difficulty can be used to explore interaction between targeting difficulty and transmission latencies in the experiment described below. (Ellis et al, 2013). ANOVA F's from raw / skew-corrected, log-transformed data are provided.…”

Section: Introductionmentioning

confidence: 99%

“…Performance under misalignments not aligned with participants' canonical axes(Ellis et al, 2013). ANOVA F's from raw / skew-corrected, log-transformed data are provided.…”

mentioning

confidence: 99%

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Interaction of Movement Difficulty due to the Misalignment Effect and Response Latency

Ellis

Adelstein

2014

Proceedings of the Human Factors and Ergonomics Society Annual

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In previous reports we measured and analyzed the Misalignment Effect Function, a function describing the decrement in human performance due to rotation between operators' display and control axes. This prior work allowed us to determine difficulty-matched sets of rotations for a generalized 3D Fitts-like movement task. We consequently are now able to study the interaction of system latency and movement difficulty in a highly generalized way in a virtual telerobotic environment using wide variety of conditions and targets. Our targets are located on a spherical shell near our participants' starting point in a high dynamic fidelity virtual environment. Analysis of participants' ability to make movements to these targets has revealed a purely multiplicative interaction between control latency and task difficulty. Interestingly, we show that this the observed interaction supports work on Fitts' Law by E.R. Hoffmann and that it depends upon accounting for an internal human processing latency of ~250 ms. Our data suggest that the interaction varies nonlinearly due to task difficulty in a manner consistent with Hoffmann's results. We propose a descriptive equation to reflect the observed interaction that can be seen as a spatiotemporal generalization of Fitts' Law. Our results provide a basis for generalizing latency requirements for reference tasks that may be varied in difficulty in a manner analogous to the Fitts' Index of Difficulty.

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Section: Introductionsupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Performance under misalignments not aligned with participants' canonical axes(Ellis et al, 2013). ANOVA F's from raw / skew-corrected, log-transformed data are provided.…”

mentioning

confidence: 99%

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