1,145 research outputs found
Efficient conservative collision detection for populated virtual worlds
Large virtual worlds, with considerable level of detail are starting to emerge everywhere, from large areas of
actual cities to archaeological detailed reconstructions of sites. Populating a virtual world adds an extra touch
to the visualization of these worlds, but unfortunately it also brings an extra burden to the system. Several tasks
are required when adding animated characters to a virtual world, such as collision detection, path planning and
other AI algorithms, rendering of dynamic geometry, amongst others. In here a method for efficient and scalable
conservative collision detection, that is able to deal with large scenes and thousands of avatars, is presented. This
method does not perform exact collision detection, hence it is conservative. The method is suitable as a basis for
path planning algorithms and other AI algorithms where an avatar is often regarded as âsomethingâ that can be
bounded by a cylinder, or a box. The algorithm is capable of dealing with arbitrarily complex 3D worlds, and
does not require any a priori knowledge of the geometry
Efficient conservative collision detection for populated virtual worlds
Large virtual worlds, with considerable level of detail are starting to emerge everywhere, from large areas of actual cities to archaeological reconstructions of large sites. Populating a virtual world adds an extra touch to the visualization of these worlds, but unfortunately it also brings an extra burden to the system. Several tasks are required when adding animated characters to a virtual world, such as collision detection, path planning and other AI algorithms, rendering of dynamic geometry, amongst others. In here a method for efficient and scalable conservative collision detection is presented, that is able to deal with large scenes and thousands of avatars. This method does not perform exact collision detection, hence it is conservative. The method is suitable as a basis for path planning algorithms and other AI algorithms where an avatar is often regarded as 'something' that can be bounded by a cylinder, or a box. The algorithm is capable of dealing with arbitrarily complex 3D worlds, and does not require any a priori knowledge of the geometry.ACM Siggraph, EG, GGC
Path planning for complex 3D multilevel environments
The continuous development of graphics hardware is
contributing to the creation of 3D virtual worlds with
high level of detail, from models of large urban areas, to
complete infrastructures, such as residential buildings,
stadiums, industrial settings or archaeological sites, to
name just a few. Adding virtual humans or avatars adds
an extra touch to the visualization providing an enhanced
perception of the spaces, namely adding a sense of scale,
and enabling simulations of crowds. Path planning for
crowds in a meaningful way is still an open research
field, particularly when it involves an unknown polygonal
3D world. Extracting the potential paths for navigation in
a non automated fashion is no longer a feasible option
due to the dimension and complexity of the virtual
environments available nowadays. This implies that we
must be able to automatically extract information from
the geometry of the unknown virtual world to define
potential paths, determine accessibilities, and prepare a
navigation structure for real time path planning and path
finding. A new image based method is proposed that
deals with arbitrarily a priori unknown complex virtual
worlds, namely those consisting of multilevel passages
(e.g. over and below a bridge). The algorithm is capable
of extracting all the information required for the actual
navigation of avatars, creating a hierarchical data
structure to help both high level path planning and low
level path finding decisions. The algorithm is image
based, hence it is tessellation independent, i.e. the
algorithm does not rely on the underlying polygonal
structure of the 3D world. Therefore, the number of
polygons does not have a significant impact on the
performance, and the topology has no weight on the
results.Fundação para a CiĂȘncia e a Tecnologi
Path planning for complex 3D multilevel environments
The continuous development of graphics hardware is
contributing to the creation of 3D virtual worlds with
high level of detail, from models of large urban areas, to
complete infrastructures, such as residential buildings,
stadiums, industrial settings or archaeological sites, to
name just a few. Adding virtual humans or avatars adds
an extra touch to the visualization providing an enhanced
perception of the spaces, namely adding a sense of scale,
and enabling simulations of crowds. Path planning for
crowds in a meaningful way is still an open research
field, particularly when it involves an unknown polygonal
3D world. Extracting the potential paths for navigation in
a non automated fashion is no longer a feasible option
due to the dimension and complexity of the virtual
environments available nowadays. This implies that we
must be able to automatically extract information from
the geometry of the unknown virtual world to define
potential paths, determine accessibilities, and prepare a
navigation structure for real time path planning and path
finding. A new image based method is proposed that
deals with arbitrarily a priori unknown complex virtual
worlds, namely those consisting of multilevel passages
(e.g. over and below a bridge). The algorithm is capable
of extracting all the information required for the actual
navigation of avatars, creating a hierarchical data
structure to help both high level path planning and low
level path finding decisions. The algorithm is image
based, hence it is tessellation independent, i.e. the
algorithm does not use the underlying polygonal structure
of the 3D world. Therefore, the number of polygons as
well as the topology, do not affect the performance
Autonomous agents and avatars in REVERIEâs virtual environment
In this paper, we describe the enactment of autonomous agents and avatars in the web-based social collaborative virtual environment of REVERIE that supports natural, human-like behavior, physical interaction and engagement. Represented by avatars, users feel immersed in this virtual world in which they can meet and share experiences as in real life. Like the avatars, autonomous agents that may act in this world are capable of demonstrating human-like non-verbal behavior and facilitate social interaction. We describe how reasoning components of the REVERIE system connect and cooperatively control autonomous agents and avatars representing a user
Analysis domain model for shared virtual environments
The field of shared virtual environments, which also
encompasses online games and social 3D environments, has a
system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model
Agent Street: An Environment for Exploring Agent-Based Models in Second Life
Urban models can be seen on a continuum between iconic and symbolic. Generally speaking, iconic models are physical versions of the real world at some scaled down representation, while symbolic models represent the system in terms of the way they function replacing the physical or material system by some logical and/or mathematical formulae. Traditionally iconic and symbolic models were distinct classes of model but due to the rise of digital computing the distinction between the two is becoming blurred, with symbolic models being embedded into iconic models. However, such models tend to be single user. This paper demonstrates how 3D symbolic models in the form of agent-based simulations can be embedded into iconic models using the multi-user virtual world of Second Life. Furthermore, the paper demonstrates Second Life\'s potential for social science simulation. To demonstrate this, we first introduce Second Life and provide two exemplar models; Conway\'s Game of Life, and Schelling\'s Segregation Model which highlight how symbolic models can be viewed in an iconic environment. We then present a simple pedestrian evacuation model which merges the iconic and symbolic together and extends the model to directly incorporate avatars and agents in the same environment illustrating how \'real\' participants can influence simulation outcomes. Such examples demonstrate the potential for creating highly visual, immersive, interactive agent-based models for social scientists in multi-user real time virtual worlds. The paper concludes with some final comments on problems with representing models in current virtual worlds and future avenues of research.Agent-Based Modelling, Pedestrian Evacuation, Segregation, Virtual Worlds, Second Life
Collision detection: review of methods and recent advances in crowd simulation
Crowd simulation is a large complex system that visualizes the behavior of crowd entities' movement and their interactions with the virtual environment. Crowd model is usually integrated into a virtual environment to make the environment alive. In the context of agent-based simulation (as in crowd simulation), it encompasses collision checking between moving agents that are present in the same environment. Hence, it is important to design an efficient and yet effective collision detection in crowd simulation. This is to ensure that it is cost effective toward computational processing usage and still produce a believable behavior. This paper presents a study of collision detection techniques in crowd models, and recent advancement to accelerate the process so that in turn, these efforts could also improve the performance and outcome of crowd model in virtual environment applications
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