Distant Object Manipulation with Adaptive Gains in Virtual Reality

Liu, Xiaolong; Wang, Lili; Luan, Shuai; Shi, Xuehuai; Liu, Xinda

doi:10.1109/ismar55827.2022.00092

Cited by 4 publications

(3 citation statements)

References 25 publications

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“…On the other hand, participants who possess good depth perception skills and maintain a steady hand find adaptive gain less advantageous, as it can introduce complexity to the interaction by necessitating adjustment to the virtual hand's speed. Although we did not find evidence of performance difference in completion time and trajectory length, the evidence of difference in number of attempts suggests adaptive gain requires more effort to complete the task, which contradicts some existing research [57,92]. The possible reason could be that our study only featured a threshold-based implementation of adaptive gain, and the impact of such an adaptive gain function is only noticeable from post-study feedback.…”

Section: Discussioncontrasting

confidence: 99%

“…We deliberated on whether to employ a linear upscaling function or a non-linear upscaling function in the extension phrase. A linear upscaling function is intuitively comprehensible and easy to learn, whereas a non-linear upscaling function can potentially offer greater flexibility during the extension [4,20,57,92]. Therefore, our first user study evaluates the difference of linear gain and non-linear gain for extendable hand interaction.…”

Section: User Study 1: Linear Gain or Adaptive Gainmentioning

confidence: 99%

See 1 more Smart Citation

Precise Embodied Data Selection with Haptic Feedback while Retaining Room-Scale Visualisation Context

Dai,

Li,

Ens

et al. 2023

Preprint

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Focus-and-context techniques allow visualisation users to keep a full dataset in view while making detailed selections. Such techniques have been studied extensively on desktop to allow precise selection within large data sets, but they have not been explored in immersive 3D modalities. In this paper we develop a novel immersive focus-and-context technique based on a "magic portal" metaphor for precise data-point selection within larger-than-room-scale 3D scatter plots. We compare linear and non-linear gain "Go-Go arm" implementations reaching to place the portal, finding that non-linear gain may help people who have difficulty judging depth at a distance. We find strong evidence that portals reduce overshoots in selection and overall hand trajectory length. The portals also enable us to use a robot arm to provide haptic feedback within the limited volume of the portal region. We demonstrate applications for portal-based selection through two use-case scenarios.

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Section: Discussioncontrasting

confidence: 99%

Section: User Study 1: Linear Gain or Adaptive Gainmentioning

confidence: 99%

Precise Embodied Data Selection with Haptic Feedback while Retaining Room-Scale Visualisation Context

Dai,

Li,

Ens

et al. 2023

Preprint

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“…Furthermore, it only supports 6DoF simultaneous translation and rotation, which is often suitable for large or rough transformations [18]. In addition to velocity scaling, an adaptive gain approach was recently proposed to improve the accuracy and efficiency of distant object manipulation [25]. Gains are calculated through fitting user data collected during object manipulation.…”

Section: Related Workmentioning

confidence: 99%

Comparing and Contrasting Near-Field, Object Space, and a Novel Hybrid Interaction Technique for Distant Object Manipulation in VR

Hsieh,

Chien,

Brickler

et al. 2024

Virtual Worlds

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In this contribution, we propose a hybrid interaction technique that integrates near-field and object-space interaction techniques for manipulating objects at a distance in virtual reality (VR). The objective of the hybrid interaction technique was to seamlessly leverage the strengths of both the near-field and object-space manipulation techniques. We employed bimanual near-field metaphor with scaled replica (BMSR) as our near-field interaction technique, which enabled us to perform multilevel degrees-of-freedom (DoF) separation transformations, such as 1~3DoF translation, 1~3DoF uniform and anchored scaling, 1DoF and 3DoF rotation, and 6DoF simultaneous translation and rotation, with enhanced depth perception and fine motor control provided by near-field manipulation techniques. The object-space interaction technique we utilized was the classic Scaled HOMER, which is known to be effective and appropriate for coarse transformations in distant object manipulation. In a repeated measures within-subjects evaluation, we empirically evaluated the three interaction techniques for their accuracy, efficiency, and economy of movement in pick-and-place, docking, and tunneling tasks in VR. Our findings revealed that the near-field BMSR technique outperformed the object space Scaled HOMER technique in terms of accuracy and economy of movement, but the participants performed more slowly overall with BMSR. Additionally, our results revealed that the participants preferred to use the hybrid interaction technique, as it allowed them to switch and transition seamlessly between the constituent BMSR and Scaled HOMER interaction techniques, depending on the level of accuracy, precision and efficiency required.

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