TeslaMirror: Multistimulus Encounter-Type Haptic Display for Shape and Texture Rendering in VR

Fedoseev, Aleksey; Tleugazy, Akerke; Labazanova, Luiza; Tsetserukou, Dzmitry

doi:10.1145/3388534.3407300

Cited by 4 publications

(4 citation statements)

References 4 publications

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“…A variety of active devices have been explored by researchers, such as drones [1,97], desk robot [40] or other customised devices [83]. Our system is based on a robot-arm to precisely place haptic proxies with provide firm resistance [7,30,37,61,86]. Most existing research with encountered-type haptics focus on providing a similar interaction experience to interacting with a physical object.…”

Section: Encountered-type Hapticsmentioning

confidence: 99%

“…Mercado et al used a robot arm for on-demand interaction with a physical plane mimicking surfaces like table or wall [61]. Fedoseev et al combined a robot arm on actuated wheels with a surface changing device to simulate the touch of objects with different shapes [37]. However, limited research has discussed haptic feedback to support "superpower" experiences, or, as Parastoo et al described, the Beyond Being Real experience [3].…”

Section: Encountered-type Hapticsmentioning

confidence: 99%

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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: Encountered-type Hapticsmentioning

confidence: 99%

Section: Encountered-type Hapticsmentioning

confidence: 99%

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

Dai,

Li,

Ens

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…For example, Lee et al [43] developed a remote control approach to manipulate the robot end effector movement with hand gestures through virtual reality controllers. Robot arms are also widely used in encountered-type haptics to continuously follow and match the user's actions [3,22,52,72]. For example, Araujo et al [3] used a robot arm to provide feeling of textures through a tactile device on a robot arm and simple interactions through buttons.…”

Section: Encountered-type Hapticsmentioning

confidence: 99%

RoboHapalytics: A Robot Assisted Haptic Controller for Immersive Analytics

Dai

Smiley

Dwyer

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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“…Fedoseev et al [13] proposed a linkage array for tactile rendering with an encountered-type haptic display. Fani et al [14] implemented the system where mechanotactile feedback was used at several point on human arm to improve the telemanipulation of a robotic arm in a dexterous operation.…”

mentioning

confidence: 99%

DeepXPalm: Tilt and Position Rendering using Palm-worn Haptic Display and CNN-based Tactile Pattern Recognition

Cabrera

Oleg

Jonathan

et al. 2022

2022 IEEE Haptics Symposium (HAPTICS)

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Telemanipulation of deformable objects requires high precision and dexterity from the users, which can be increased by kinesthetic and tactile feedback. However, the object shape can change dynamically, causing ambiguous perception of its alignment and hence errors in the robot positioning. Therefore, the tilt angle and position classification problem has to be solved to present a clear tactile pattern to the user. This work presents a telemanipulation system for plastic pipettes consisting of a multi-contact haptic device LinkGlide to deliver haptic feedback at the users' palm and two tactile sensors array embedded in the 2-finger Robotiq gripper. We propose a novel approach based on Convolutional Neural Networks (CNN) to detect the tilt and position while grasping deformable objects. The CNN generates a mask based on recognized tilt and position data to render further multi-contact tactile stimuli provided to the user during the telemanipulation. The study has shown that using the CNN algorithm and the preset mask, tilt, and position recognition by users is increased from 9.67% using the direct data to 82.5%.

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TeslaMirror: Multistimulus Encounter-Type Haptic Display for Shape and Texture Rendering in VR

Abstract: Figure 1: (a) TeslaMirror architecture. (b) User approaching the virtual surface. (c) Real-time simulation by haptic display.

Cited by 4 publications

References 4 publications

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

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

RoboHapalytics: A Robot Assisted Haptic Controller for Immersive Analytics

DeepXPalm: Tilt and Position Rendering using Palm-worn Haptic Display and CNN-based Tactile Pattern Recognition

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