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Felix Huppert

dblp:249/4012 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2021
—ORCID · none

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

Human-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
Accessibility and assistive technology · 44% Haptics and multimodal interaction · 44% Human-robot interaction · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Accessibility and assistive technology
assistive navigation
0.512021
GuideCopter - A Precise Drone-Based Haptic Guidance Interface for Blind or Visually Impaired People · CHI 2021
Haptics and multimodal interaction
haptic feedback
0.512021
GuideCopter - A Precise Drone-Based Haptic Guidance Interface for Blind or Visually Impaired People · CHI 2021

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

pilot study · 0.5comparative user study · 0.5
YearPublicationVenuePosition
2021 GuideCopter - A Precise Drone-Based Haptic Guidance Interface for Blind or Visually Impaired People
abstract
Drone assisted navigation aids for supporting walking activities of visually impaired have been established in related work but fine-point object grasping tasks and the object localization in unknown environments still presents an open and complex challenge. We present a drone-based interface that provides fine-grain haptic feedback and thus physically guides them in hand-object localization tasks in unknown surroundings. Our research is built around community groups of blind or visually impaired (BVI) people, which provide in-depth insights during the development process and serve later as study participants. A pilot study infers users’ sensibility to applied guiding stimuli forces and the different human-drone tether interfacing possibilities. In a comparative follow-up study, we show that our drone-based approach achieves greater accuracy compared to a current audio-based hand guiding system and delivers overall a more intuitive and relatable fine-point guiding experience.
Felix Huppert, Gerold Hölzl, Matthias Kranz
CHI1