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Xianshi Xie

dblp:86/8320 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2012
—ORCID · none

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

Human-computer interaction and ubiquitous computing · 2 · 2 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

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 · 77% Immersive interaction · 23%
Computer graphics and multimedia
1 paper
Virtual and augmented reality · 100%

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

TopicWeightPapersLastEvidence papers
Human-robot interaction › human-robot interface
mixed reality human-robot interaction
0.112012
Immersion with robots in large virtual environments · HRI 2012
Virtual and augmented reality › locomotion
redirected walking
0.012012
Immersion with robots in large virtual environments · HRI 2012
Immersive interaction › virtual reality experience
immersion
0.012012
Immersion with robots in large virtual environments · HRI 2012

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

redirected walking · 0.3mixed reality system · 0.3
YearPublicationVenuePosition
2012 Distributed spatial memory in virtual human-robot team scenarios
abstract
This experiment investigates the spatial memory and attention when human acts as supervisor of one or two groups of distributed robot teams in a large virtual environment (VE). The problem is similar to learning a new environment and interpreting its spatial structure, e.g., [Mou and McNamara 2002], but less is known when attention is divided or locomotion is involved. Our motivation arises in the context of humans and robots acting cooperatively together as a team. Such teaming is becoming increasingly important in many scenarios, such as disaster relief, and wilderness search and rescue [Humphrey and Adams 2009].
Xianshi Xie, Julie A. Adams, Timothy P. McNamara, Bobby Bodenheimer
SAP1
2012 Immersion with robots in large virtual environments
abstract
This paper presents a mixed reality system for combining real robots, humans, and virtual robots. The system tracks and controls physical robots in local physical space, and inserts them into a virtual environment (VE). The system allows a human to locomote in a VE larger than the physically tracked space of the laboratory through a form of redirected walking. An evaluation assessed the conditions under which subjects found the system to be the most immersive.
Xianshi Xie, Qiufeng Lin, Julie A. Adams, Bobby Bodenheimer
HRI1