Design and implementation of a collaborative virtual haptic surgical training system

Chebbi, Brahim; Lazaroff, D.; Bogsany, F.; Liu, P.X.; Ni, Liya Grace; Rossi, Marcia

doi:10.1109/icma.2005.1626566

Cited by 46 publications

(22 citation statements)

References 8 publications

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“…Figure 1 shows a multilateral teleoperation system made up of robots. One potential application scenario for Figure 1 is that − 1 master's robots are sharing the execution of a task in a remote environment by collaboratively controlling the movement of a slave robot [4][5] [6][7] [8]. In Figure 1, each human operator/master interaction is denoted by ℎ , = 1, … , − 1 and the slave/environment interaction is denoted by .…”

Section: Motivationmentioning

confidence: 99%

A method for passivity analysis of multilateral haptic systems

Mendez

Tavakoli

2014

Advanced Robotics

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This paper presents a novel criterion to study the stability of multilateral teleoperation systems based on passivity. Such systems (modelled as -port networks) have recently found interesting applications in cooperative haptic teleoperation and haptic-assisted training. The criterion provides researchers with an analytical, closed-form, necessary and sufficient condition useful for both analysis and design of multilateral haptic teleoperation systems. The paper shows that when = 2 the proposed conditions reduce to the wellknown Raisbeck's passivity criterion for 2-port networks. The proposed conditions are used to study the passivity (and consequently the stability) of a dual-user haptic system for control of a single teleoperated robot. Simulations and experiments are performed to further test the validity of the proposed criterion.

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Section: Motivationmentioning

confidence: 99%

A method for passivity analysis of multilateral haptic systems

Mendez

Tavakoli

2014

Advanced Robotics

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“…that require the ability to interact bidirectionally with remote real/virtual surroundings have driven haptics research worldwide. Multimedia research has recognized the potential of haptics also for indirect interpersonal communication in collaborative haptic assembly tasks [1], or remote training of contact-intensive tasks such as surgery [2].…”

Section: Introductionmentioning

confidence: 99%

Perceptual and Bitrate-Scalable Coding of Haptic Surface Texture Signals

Chaudhari

Schuwerk

Danaei

et al. 2015

IEEE J. Sel. Top. Signal Process.

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Abstract-Applications involving indirect interpersonal communication, such as collaborative design/assembly/exploration of physical objects, can benefit strongly from the transmission of contact-based haptic media, in addition to the more traditional audiovisual media. Inclusion of haptic media has been shown to improve immersiveness, task performance, and the overall experience of task execution. While several decades of research have been dedicated to the acquisition, processing, coding, and display of audio and video streams, similar aspects for haptic streams have been addressed only recently.Simultaneous masking is a perceptual phenomenon widely exploited in the compression of audio data. In the first part of this paper, to the best of our knowledge, we present first-time empirical evidence for masking in the perception of wideband vibrotactile signals. Our results show that this phenomenon for haptics is very similar to its auditory analog. Signals closer in frequency to a powerful masker (25 dB above detection threshold) are masked more strongly (peak threshold-shifts of up to 28 dB) than those away from the masker (threshold-shifts of 15-20 dB). The masking curves approximately follow the masker's spectral profile. In the second part of this paper, we present a bitrate scalable haptic texture codec, which incorporates the masking model and describe its subjective and objective performance evaluation. Experiments show that we can drive down the codec output bitrate to a very low value of 2.3 kbps, without the subjects being able to reliable discriminate between the codec input and distorted output texture signals.

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“…Haptic feedback has the potential to provide redundant feedback, which would greatly improve the saliency of signals, as well as provide a unique feedback as a new signal to reinforce or improve user understanding (Robles-de-la-Torre, 2006). Haptic technology has found many successful applications such as surgical simulation (e.g., Basdogan et al, 2004;Chebbi et al, 2005), medical training (e.g., Coles, Meglan, & John, 2011), virtual prototyping (Zhu & Lee, 2004), scientific visualization (e.g., Lawrence, Pao, Lee, & Novoselov, 2004), and assistive technology for users with visual impairments (e.g., Amemiya & Sugiyama, 2010) or motionimpaired users (e.g., Keates, Hwang, Langdon, Clarkson, & Robinson, 2002). Many studies have also shown that haptic feedback can improve user performance in various tasks (Dinse et al, 2005;Richard & Coiffet, 1995), enhance the sense of sharing and each user's perception on his or her partner's actions (Hubbold, 2002), and increase perceived togetherness (Basdogan, Ho, Srinivasan, & Slater, 2000;Sallnas, RassmusGröhn, & Sjöström, 2000;Slater, Sadagic, Usoh, & Schroeder, 2000).…”

Section: Introductionmentioning

confidence: 99%