Rendering 3D virtual objects in mid-air using controlled magnetic fields

Adel, Alaa; Seif, Mohamed Abou; Hölzl, Gerold; Kranz, Matthias; Abdennadher, Slim; Khalil, Islam S. M.

doi:10.1109/iros.2017.8202179

Cited by 7 publications

(4 citation statements)

References 20 publications

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“…Mid-air haptics is an emerging group of technologies for providing haptic sensations at a distance, without any direct physical contact with the interface creating the stimuli. Several physical principles can be used to provide midair haptic stimuli: magnetism [1], acoustics [2], electric arcs [3], optics [4], and aerodynamics [5]. Among these technologies, the currently most mature one uses focused airborne ultrasound.…”

Section: Introductionmentioning

confidence: 99%

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Investigating the Recognition of Local Shapes Using Mid-air Ultrasound Haptics

Howard

Gallagher

Lécuyer

et al. 2019

2019 IEEE World Haptics Conference (WHC)

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Mid-air haptics technologies are able to convey haptic sensations without any direct contact between the user and the haptic interface. One representative example of this technology is ultrasound haptics, which uses ultrasonic phased arrays to deliver haptic sensations. Research on ultrasound haptics is only in its beginnings, and the literature still lacks principled perception studies in this domain. This paper presents a series of human subject experiments investigating important perceptual aspects related to the rendering of 2D shapes by an ultrasound haptic interface (the Ultrahaptics STRATOS platform). We carried out four user studies aiming at evaluating (i) the absolute detection threshold for a static focal point rendered via amplitude modulation, (ii) the absolute detection and identification thresholds for line patterns rendered via spatiotemporal modulation, (iii) the ability to discriminate different line orientations, and (iv) the ability to perceive virtual bumps and holes. These results shed light on the rendering capabilities and limitations of this novel technology for 2D shapes.

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Section: Introductionmentioning

confidence: 99%

“…This research has received funding from the EU's H2020 research and innovation programme (grant agreement No 801413, project "H-Reality"). 1 T. Howard and C. Pacchierotti are with Univ Rennes, IRISA, CNRS, Inria -Rennes, France.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Recognition of Local Shapes Using Mid-air Ultrasound Haptics

Howard

Gallagher

Lécuyer

et al. 2019

2019 IEEE World Haptics Conference (WHC)

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“…Yang et al (2016) implemented a small actuator that can oscillate a wide frequency band using unstable mass. Adel et al (2017) implemented force feedback by controlling the magnetic fields and mapping the magnetic force between the magnet placed on fingers and the electromagnetic plate. Although there are drawbacks that it can be used only in a limited area, the range of force that can be passed is wide, thus it is possible to implement more precise resolution in the future, and by wearing relatively light equipment, operators can feel more natural and accurate environmental information from the robot site.…”

Section: Multimodal Feedback Schemementioning

confidence: 99%

Robotic remote control based on human motion via virtual collaboration system: A survey

Jung

Song

2018

JAMDSM

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This paper offers a review of the latest robotic remote control schemes that are based on human motion through the virtual collaboration system. The robotic remote control schemes have been studied and developed to combine the intelligence of humans with the precision and mechanical strength of robots. They have performed an important role in some dangerous environments by replacing humans in many difficult jobs, but the lack of intuitive control interfaces causes decreased efficiency. To address this problem, various approaches have been recently investigated, including human motion-based control, visual feedback systems, tactile or force feedback, and other various haptic systems. This paper describes the tendencies of these efforts and discusses possibilities and limitations in three parts: remote control based on human motion, multimodal feedback schemes for realistic interaction, and virtual collaboration systems.

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“…The second type produces static magnetic forces regardless of the position of the operator. The implication of using this technique is that it requires a relatively large number of coils to render all features of complex objects [Adel 2017]. This problem has been solved by the incorporation of a position-sensing device into the haptic system [Adel 2018], and an impedance-type haptic rendering algorithm has been implemented using an optical localization device.…”

Section: Introductionmentioning

confidence: 99%

Magnetic Localization for an Electromagnetic-Based Haptic Interface

et al. 2019

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In this letter, we develop a magnetic localization system for an electromagnetic-based haptic interface (EHI). Haptic interaction is achieved using a controlled magnetic force applied via an EHI on a magnetic dipole attached to a wearable finger splint. The position of the magnetic dipole is estimated using two identical arrays of three-dimensional magnetic field sensors in order to eliminate the magnetic field generated by the EHI. The measurements of these arrays are used to estimate the position of the magnetic dipole by an artificial neural network. This network maps the field readings to the position of the magnetic dipole. The proposed system is experimentally validated under four cases of the magnetic field generated by the EHI. These cases are likely to be encountered during the haptic rendering of virtual shapes. In the absence of the magnetic field, the mean absolute position error (MAE) is 0.80 ± 0.30 mm (n = 125). Static and sinusoidal magnetic fields are applied, and the MAEs are 1.26 ± 0.43 mm (n = 125) and 0.91 ± 0.33 mm (n = 125), respectively. A random time-varying magnetic field is applied, and the MAE is 0.86 ± 0.33 mm (n = 125). Our statistical analysis shows that the repeatability of the magnetic localization is acceptable regardless of the field generated by the EHI, at α = 0.05 and 95% confidence level.

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Rendering 3D virtual objects in mid-air using controlled magnetic fields

Cited by 7 publications

References 20 publications

Investigating the Recognition of Local Shapes Using Mid-air Ultrasound Haptics

Investigating the Recognition of Local Shapes Using Mid-air Ultrasound Haptics

Robotic remote control based on human motion via virtual collaboration system: A survey

Magnetic Localization for an Electromagnetic-Based Haptic Interface

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