Closed loop application of electroadhesion for increased precision in texture rendering
January 07, 2020 Β· Declared Dead Β· π IEEE Transactions on Haptics
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Roman V. Grigorii, J. Edward Colgate
arXiv ID
2001.01868
Category
cs.HC: Human-Computer Interaction
Citations
9
Venue
IEEE Transactions on Haptics
Last Checked
4 months ago
Abstract
Tactile displays based on friction modulation offer wide-bandwidth forces rendered directly on the fingertip. However, due to a number of touch conditions (e.g., normal force, skin hydration) that result in variations in the friction force and the strength of modulation effect, the precision of the force rendering remains limited. In this paper we demonstrate a closed-loop electroadhesion method for precise playback of friction force profiles on a human finger and we apply this method to the tactile rendering of several textiles encountered in everyday life.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted