Demo Data from EDBT 2026 / reviewers in the wild / expert
Jean-Baptiste Chossat
dblp:164/8412
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0003-2264-5830ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-authorSystems, architecture and hardware · 2 · 1 first-authorHuman-computer interaction and ubiquitous computing · 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
3 papers |
Haptics and multimodal interaction · 67% Human-robot interaction · 14% Wearable and physiological sensing · 12% | |
| Artificial intelligence
1 paper |
Robot manipulation · 100% |
Topics — the 8 heaviest of 10, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Haptics and multimodal interaction › haptic device control
grasp force control |
0.2 | 1 | 2016 | Haptic feedback for improved robotic arm control during simple grasp, slippage, and contact detection tasks · ICRA 2016 |
Haptics and multimodal interaction
haptic feedback |
0.2 | 1 | 2016 | Haptic feedback for improved robotic arm control during simple grasp, slippage, and contact detection tasks · ICRA 2016 |
Human-robot interaction
teleoperation |
0.2 | 1 | 2016 | Haptic feedback for improved robotic arm control during simple grasp, slippage, and contact detection tasks · ICRA 2016 |
Haptics and multimodal interaction › haptic feedback
vibrotactile feedback |
0.2 | 1 | 2016 | Haptic feedback for improved robotic arm control during simple grasp, slippage, and contact detection tasks · ICRA 2016 |
Immersive interaction
virtual reality controller |
0.1 | 1 | 2019 | HaptiVec: Presenting Haptic Feedback Vectors in Handheld Controllers using Embedded Tactile Pin Arrays · CHI 2019 |
Robotics › Robot manipulation
grasping |
0.1 | 1 | 2016 | Haptic feedback for improved robotic arm control during simple grasp, slippage, and contact detection tasks · ICRA 2016 |
Robotics › Robot manipulation › tactile sensing
slip detection |
0.1 | 1 | 2016 | Haptic feedback for improved robotic arm control during simple grasp, slippage, and contact detection tasks · ICRA 2016 |
Haptics and multimodal interaction › tactile sensing
artificial skin |
0.1 | 1 | 2015 | Wearable soft artificial skin for hand motion detection with embedded microfluidic strain sensing · ICRA 2015 |
Methods — techniques the papers use, named apart from their topics
user study · 0.5tactile pin array · 0.4pressure vector rendering · 0.4microfluidic strain sensing · 0.2liquid metal wiring · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | HaptiVec: Presenting Haptic Feedback Vectors in Handheld Controllers using Embedded Tactile Pin ArraysabstractHaptiVec is a new haptic feedback paradigm for handheld controllers which allows users to feel directional haptic pressure vectors on their fingers and hands while interacting with virtual environments. We embed a 3 by 5 tactile pin array (with an average pin spacing of 25 mm) into the handles of two custom VR type controllers. By presenting directional pressure vectors in eight cardinal directions (N, NE, E, SE, S, SW, W, NW) to users without prior training, they were able to distinguish the correct direction with an accuracy of at least 79%. We illustrate two applications where our device enhances virtual experiences over traditional vibrotactile feedback. In the first application, through the classic first-person shooter Doom, we demonstrate that users can receive directional pressure feedback corresponding to the direction of incident enemy projectiles. In the second application, we demonstrate how our controller can create a more immersive experience by allowing the user to feel their virtual climate by randomizing the directional vectors and presenting the user with "haptic rain" which adapts with the intensity of the rainfall. Daniel K. Y. Chen, Jean-Baptiste Chossat, Peter B. Shull |
CHI | 2 |
| 2016 | Haptic feedback for improved robotic arm control during simple grasp, slippage, and contact detection tasksabstractThis paper explores the use of haptic and visual feedback during routine object-manipulation tasks. We conducted tests of slippage detection, contact detection, and grasp control, with the help of twelve human participants. During the tests, the subjects controlled the robotic arm of a UR5 Universal Robot that was mounted with a three-finger robotic gripper and equipped with tactile sensors. The participants used either their visual feedback, vibrotactile feedback, or pressure feedback to assess the movements of the robotic fingers as they attempted to complete each task. We analyzed their performance with each type of feedback in order to evaluate how haptic feedback may be used to reduce the need for visual attention, and thus improve the lives of upper-limb amputees. M. Reza Motamedi, Jean-Baptiste Chossat, Jean-Philippe Roberge, Vincent Duchaine |
ICRA | 2 |
| 2015 | Wearable soft artificial skin for hand motion detection with embedded microfluidic strain sensingabstractThis paper describes the design and manufacturing of soft artificial skin with an array of embedded soft strain sensors for detecting various hand gestures by measuring joint motions of five fingers. The proposed skin was made of a hyperelastic elastomer material with embedded microchannels filled with two different liquid conductors, an ionic liquid and a liquid metal. The ionic liquid microchannels were used to detect the mechanical strain changes of the sensing material, and the liquid metal microchannels were used as flexible and stretchable electrical wires for connecting the sensors to an external control circuit. The two heterogeneous liquid conductors were electrically interfaced through flexible conductive threads to prevent the two liquid from being intermixed. The skin device was connected to a computer through a microcontroller instrumentation circuit for reconstructing the 3-D hand motions graphically. The paper also presents preliminary calibration and experimental results. Jean-Baptiste Chossat, Yiwei Tao, Vincent Duchaine, Yong-Lae Park |
ICRA | 1 |