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Jason T. Nolin

dblp:99/2167 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Haptics and multimodal interaction · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Haptics and multimodal interaction › haptic simulation
cutting simulation
0.012003
The haptic scissors: cutting in virtual environments · ICRA 2003
Haptics and multimodal interaction › haptic feedback
force feedback
0.012003
The haptic scissors: cutting in virtual environments · ICRA 2003
Haptics and multimodal interaction › haptic interface
haptic device design
0.012003
The haptic scissors: cutting in virtual environments · ICRA 2003

Methods — techniques the papers use, named apart from their topics

empirical tissue modeling · 0.0analytical friction modeling · 0.0
YearPublicationVenuePosition
2003 The haptic scissors: cutting in virtual environments
abstract
The "haptic scissors" is a device that creates the sensation of cutting in virtual environments. The scissors have two degrees of freedom of motion and force feedback, one for cutting (single blade rotation) and one for translation. An algorithm was developed to simultaneously display translational and cutting forces for a realistic cutting simulation. In previous work, we use filtered data from cutting biological tissues to create "haptic recordings" of the cutting experience. Here, we consider two cutting models: one based on real tissue data and one that is analytical. The model based on real tissue is a segmented linear empirical model of the original data. Experimental results show that users cannot differentiate between these models and the haptic recordings created earlier. The analytical model uses a combination of friction, assumed material properties, and user motion (position and velocity) to determine the displayed cutting forces.
Allison M. Okamura, Robert J. Webster III, Jason T. Nolin, K. W. Johnson, H. Jafry
ICRA3