Demo Data from EDBT 2026 / reviewers in the wild / expert
Chie Takahashi
dblp:301/0640
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
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 |
Human-robot interaction · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction › physical human-robot interaction
object handover |
0.6 | 1 | 2022 | Robot, Pass Me the Tool: Handle Visibility Facilitates Task-oriented Handovers · HRI 2022 |
Methods — techniques the papers use, named apart from their topics
virtual reality experiment · 0.6motion analysis · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Robot, Pass Me the Tool: Handle Visibility Facilitates Task-oriented HandoversabstractA human handing over an object modulates their grasp and movements to accommodate their partner's capa-bilities, which greatly increases the likelihood of a successful transfer. State-of-the-art robot behavior lacks this level of user understanding, resulting in interactions that force the human partner to shoulder the burden of adaptation. This paper investigates how visual occlusion of the object being passed affects the subjective perception and quantitative performance of the human receiver. We performed an experiment in virtual reality where seventeen participants were tasked with repeatedly reaching to take a tool from the hand of a robot; each of the three tested objects (hammer, screwdriver, scissors) was presented in a wide variety of poses. We carefully analysed the user's hand and head motions, the time to grasp the object, and the chosen grasp location, as well as participants' ratings of the grasp they just performed. Results show that initial visibility of the handle significantly increases the reported holdability and immediate usability of a tool. Furthermore, a robot that offers objects so that their handles are more occluded forces the receiver to spend more time in planning and executing the grasp and also lowers the probability that the tool will be grasped by the handle. Together these findings indicate that robots can more effectively support their human work partners by increasing the visibility of the intended grasp location of objects being passed. Valerio Ortenzi, Maija Filipovica, Diar Abdlkarim, Tommaso Pardi, Chie Takahashi, Alan Wing, Massimiliano Di Luca, Katherine J. Kuchenbecker |
HRI | 5 |