VIRTUOUS
by Pavel Andris, José P. Costeira, Karol Dobrovodsky, Michal
Haindl, Josef Kittler, Peter Kurdel, José Santos-Victor and Andrew
J. Stoddart
VIRTUOUS (Autonomous Acquisition of Virtual
Reality Models from Real World Scenes) is a joint research project between
the University of Surrey, Guildford, United Kingdom, Instituto Superior
Tecnico, Lisboa, Portugal, Institute of Information Theory and Automation,
Prague, Czech Republic, and the Institute of Control Theory and Robotics,
Bratislava, Slovakia financed by the Commission of the European Communities
in frame of the INCO-COPERNICUS scheme.
The objective of this 3-year project, now in its first year, is to capture
virtual reality models of real world robot cell scenes automatically, without
interaction with a human observer and then to validate these models in
a Virtual Reality Robot Arm Trainer application. To get a lifelike simulation
of the manufacturing process, it is necessary to put 3D graphic information
about all objects located in the robot workcell into the trainer. This
is tedious and error-prone work as the scene complexity increases and automation
may substantially reduce the effect of the simulation.
The goal of the project is to substantially reduce the amount of this
work by using an autonomous acquisition system. Acquired data will be used
to build a lifelike virtual reality model of the robot workcell and all
related objects. The model will be processed by a scene properties extractor
and used by the trainer.
Range and vision sensors are used to capture virtual reality models
of a robot cell, its manipulation objects and environment. Within this
project we examine two sensor systems. The first one uses multiple views
range images from a structured light range sensor together with a colour
camera affixed to a robot arm while the second mobile platform produce
colour video sequences. The video sensor is a more ambitious sensor configuration,
it has lower cost but needs more powerful software.
Different data sources have to be mutually registered and segmented
into meaningful scene objects. To make virtual worlds realistic detailed
scene models must be built. Satisfactory models require not only complex
3D shapes accorded with the captured scene, but also lifelike colour and
texture. Textures provide useful cues to a subject navigating in such a
VR environment, and they also aid in the accurate detailed reconstruction
of the environment. Virtual textures are synthesized from underlying random
fields-based models identified in the segmentation analysis step and subsequently
they are mapped to corresponding virtual surfaces. Synthetic colour textures
reduce the space and time overheads of texture in VR systems and thus they
are essential in distributed VR applications.
The trainer software consists of a visualization and robot arm control
software. In order to validate the performance of the trainer the generated
trajectories can be downloaded to a PUMA 560 industrial robot. The trainer
hardware includes a PC family computer running an already developed real-time
robot control software. The PC computer is connected to a Silicon Graphics
workstation that is used as a scene viewer. The captured models are used
to develop and test user programs for the cell without using the cell itself.
Finally, the user programs are downloaded into the cell and verified.
Producing detailed models is of generic interest to a number of different
fields. For this reason the project results will be in the form of plug
in modules for a commercial graphical system so that they can be used for
a variety of other virtual reality applications in entertainment, medicine
and manufacturing. Further information can be found in the project web
site http://www.ee.surrey.ac.uk/ Research/VSSP/virtuous/virtuous.html.
Please contact:
Michal Haindl - CRCIM
Tel: +420 2 66052350
E-mail: haindl@utia.cas.cz
