EDBT 2026 Demo / reviewers in the wild / expert
Muhammad Akmal Bin Mohammed Zaffir
dblp:341/9458
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2024
0000-0003-3753-2062ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 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 · 61% Haptics and multimodal interaction · 30% Usability and user experience research · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction › physical human-robot interaction
object handover |
0.8 | 1 | 2024 | Presentation of Robot-Intended Handover Position using Vibrotactile Interface during Robot-to-Human Handover Task · HRI 2024 |
Human-robot interaction
physical human-robot interaction |
0.8 | 1 | 2024 | Presentation of Robot-Intended Handover Position using Vibrotactile Interface during Robot-to-Human Handover Task · HRI 2024 |
Haptics and multimodal interaction › haptic feedback
vibrotactile feedback |
0.8 | 1 | 2024 | Presentation of Robot-Intended Handover Position using Vibrotactile Interface during Robot-to-Human Handover Task · HRI 2024 |
Usability and user experience research
cognitive load |
0.2 | 1 | 2024 | Presentation of Robot-Intended Handover Position using Vibrotactile Interface during Robot-to-Human Handover Task · HRI 2024 |
Methods — techniques the papers use, named apart from their topics
vibrotactile display · 0.8user study · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Presentation of Robot-Intended Handover Position using Vibrotactile Interface during Robot-to-Human Handover TaskabstractAdvancements in robot autonomy and safety have enabled close interactions, such as object handovers, with humans. During robot-to-human handovers in assembly tasks, the robot considers the state of the human to determine its optimal handover position and timing. However, humans may struggle to focus on their primary tasks because of the need to track the robot's movement. This study aims to develop a vibrotactile interface that helps humans maintain focus on their primary tasks during object reception. The interface conveys the robot-intended handover position on the human forearm by displaying the angular direction and distance relative to the human hand via vibrotactile cues. The experimental results demonstrated that the interface allowed participants to receive objects with faster reactions and completion times, with reduced head rotation towards the robot. Participants also subjectively perceived improved performance and reduced mental workload compared with the condition without the interface. Muhammad Akmal Bin Mohammed Zaffir, Takahiro Wada |
HRI | 1 |