3 research outputs found
Conceitos e métodos para apoio ao desenvolvimento e avaliação de colaboração remota utilizando realidade aumentada
Remote Collaboration using Augmented Reality (AR) shows great
potential to establish a common ground in physically distributed
scenarios where team-members need to achieve a shared goal.
However, most research efforts in this field have been devoted to
experiment with the enabling technology and propose methods to
support its development. As the field evolves, evaluation and
characterization of the collaborative process become an essential,
but difficult endeavor, to better understand the contributions of AR.
In this thesis, we conducted a critical analysis to identify the main
limitations and opportunities of the field, while situating its maturity
and proposing a roadmap of important research actions. Next, a
human-centered design methodology was adopted, involving
industrial partners to probe how AR could support their needs
during remote maintenance. These outcomes were combined with
literature methods into an AR-prototype and its evaluation was
performed through a user study. From this, it became clear the
necessity to perform a deep reflection in order to better understand
the dimensions that influence and must/should be considered in
Collaborative AR. Hence, a conceptual model and a humancentered
taxonomy were proposed to foster systematization of
perspectives. Based on the model proposed, an evaluation
framework for contextualized data gathering and analysis was
developed, allowing support the design and performance of
distributed evaluations in a more informed and complete manner.
To instantiate this vision, the CAPTURE toolkit was created,
providing an additional perspective based on selected dimensions
of collaboration and pre-defined measurements to obtain “in situ”
data about them, which can be analyzed using an integrated
visualization dashboard. The toolkit successfully supported
evaluations of several team-members during tasks of remote
maintenance mediated by AR. Thus, showing its versatility and
potential in eliciting a comprehensive characterization of the added
value of AR in real-life situations, establishing itself as a generalpurpose
solution, potentially applicable to a wider range of
collaborative scenarios.Colaboração Remota utilizando Realidade Aumentada (RA)
apresenta um enorme potencial para estabelecer um entendimento
comum em cenários onde membros de uma equipa fisicamente
distribuídos precisam de atingir um objetivo comum. No entanto, a
maioria dos esforços de investigação tem-se focado nos aspetos
tecnológicos, em fazer experiências e propor métodos para apoiar
seu desenvolvimento. À medida que a área evolui, a avaliação e
caracterização do processo colaborativo tornam-se um esforço
essencial, mas difícil, para compreender as contribuições da RA.
Nesta dissertação, realizámos uma análise crítica para identificar
as principais limitações e oportunidades da área, ao mesmo tempo
em que situámos a sua maturidade e propomos um mapa com
direções de investigação importantes. De seguida, foi adotada uma
metodologia de Design Centrado no Humano, envolvendo
parceiros industriais de forma a compreender como a RA poderia
responder às suas necessidades em manutenção remota. Estes
resultados foram combinados com métodos da literatura num
protótipo de RA e a sua avaliação foi realizada com um caso de
estudo. Ficou então clara a necessidade de realizar uma reflexão
profunda para melhor compreender as dimensões que influenciam
e devem ser consideradas na RA Colaborativa. Foram então
propostos um modelo conceptual e uma taxonomia centrada no ser
humano para promover a sistematização de perspetivas. Com base
no modelo proposto, foi desenvolvido um framework de avaliação
para recolha e análise de dados contextualizados, permitindo
apoiar o desenho e a realização de avaliações distribuídas de
forma mais informada e completa. Para instanciar esta visão, o
CAPTURE toolkit foi criado, fornecendo uma perspetiva adicional
com base em dimensões de colaboração e medidas predefinidas
para obter dados in situ, que podem ser analisados utilizando o
painel de visualização integrado. O toolkit permitiu avaliar com
sucesso vários colaboradores durante a realização de tarefas de
manutenção remota apoiada por RA, permitindo mostrar a sua
versatilidade e potencial em obter uma caracterização abrangente
do valor acrescentado da RA em situações da vida real. Sendo
assim, estabelece-se como uma solução genérica, potencialmente
aplicável a uma gama diversificada de cenários colaborativos.Programa Doutoral em Engenharia Informátic
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Supporting Multi-User Interaction in Co-Located and Remote Augmented Reality by Improving Reference Performance and Decreasing Physical Interference
One of the most fundamental components of our daily lives is social interaction, ranging from simple activities, such as purchasing a donut in a bakery on the way to work, to complex ones, such as instructing a remote colleague how to repair a broken automobile. While we interact with others, various challenges may arise, such as miscommunication or physical interference. In a bakery, a clerk may misunderstand the donut at which a customer was pointing due to the uncertainty of their finger direction. In a repair task, a technician may remove the wrong bolt and accidentally hit another user while replacing broken parts due to unclear instructions and lack of attention while communicating with a remote advisor.
This dissertation explores techniques for supporting multi-user 3D interaction in augmented reality in a way that addresses these challenges. Augmented Reality (AR) refers to interactively overlaying geometrically registered virtual media on the real world. In particular, we address how an AR system can use overlaid graphics to assist users in referencing local objects accurately and remote objects efficiently, and prevent co-located users from physically interfering with each other. My thesis is that our techniques can provide more accurate referencing for co-located and efficient referencing for remote users and lessen interference among users.
First, we present and evaluate an AR referencing technique for shared environments that is designed to improve the accuracy with which one user (the indicator) can point out a real physical object to another user (the recipient). Our technique is intended for use in otherwise unmodeled environments in which objects in the environment, and the hand of the indicator, are interactively observed by a depth camera, and both users wear tracked see-through displays. This technique allows the indicator to bring a copy of a portion of the physical environment closer and indicate a selection in the copy. At the same time, the recipient gets to see the indicator's live interaction represented virtually in another copy that is brought closer to the recipient, and is also shown the mapping between their copy and the actual portion of the physical environment. A formal user study confirms that our technique performs significantly more accurately than comparison techniques in situations in which the participating users have sufficiently different views of the scene.
Second, we extend the idea of using a copy (virtual replica) of physical object to help a remote expert assist a local user in performing a task in the local user's environment. We develop an approach that uses Virtual Reality (VR) or AR for the remote expert, and AR for the local user. It allows the expert to create and manipulate virtual replicas of physical objects in the local environment to refer to parts of those physical objects and to indicate actions on them. The expert demonstrates actions in 3D by manipulating virtual replicas, supported by constraints and annotations. We performed a user study of a 6DOF alignment task, a key operation in many physical task domains. We compared our approach with another 3D approach that also uses virtual replicas, in which the remote expert identifies corresponding pairs of points to align on a pair of objects, and a 2D approach in which the expert uses a 2D tablet-based drawing system similar to sketching systems developed for prior work by others on remote assistance. The study shows the 3D demonstration approach to be faster than the others.
Third, we present an interference avoidance technique (Redirected Motion) intended to lessen the chance of physical interference among users with tracked hand-held displays, while minimizing their awareness that the technique is being applied. This interaction technique warps virtual space by shifting the virtual location of a user's hand-held display. We conducted a formal user study to evaluate Redirected Motion against other approaches that either modify what a user sees or hears, or restrict the interaction capabilities users have. Our study was performed using a game we developed, in which two players moved their hand-held displays rapidly in the space around a shared gameboard. Our analysis showed that Redirected Motion effectively and imperceptibly kept players further apart physically than the other techniques.
These interaction techniques were implemented using an extensible programming framework we developed for supporting a broad range of multi-user immersive AR applications. This framework, Goblin XNA, integrates a 3D scene graph with support for 6DOF tracking, rigid body physics simulation, networking, shaders, particle systems, and 2D user interface primitives.
In summary, we showed that our referencing approaches can enhance multi-user AR by improving accuracy for co-located users and increasing efficiency for remote users. In addition, we demonstrated that our interference-avoidance approach can lessen the chance of unwanted physical interference between co-located users, without their being aware of its use