Cel
The aims of the VOILA project were to carry out a collaborative programme of research on the development of flexible, dynamic vision systems and to prove their feasibility for application to a range of tasks in the operation of robot vehicles in a variety of industrial and commercial environments.
The development of the 4 experimental platforms and vision vehicle demonstrations in the VOILA project is detailed. The main vision research activities in the project are outlined and areas of research of particular importance that enabled the platforms to be established are available. The transfer of this research to the platforms has been described and the performance of the systems implemented. In particular, it has been shown how the successful transfer of some of the latest vision research to these experimental platforms and demonstrations and their implementation on multiprocessor computer systems has enabled a number of systems to be developed that provide concrete evidence that passive machine vision can provide the capabilities and performance for this type of industrial application.
The aims of the project were to carry out a collaborative programme of research on the development of flexible, dynamic vision systems and to prove their feasibility for application to a range of tasks in the operation of robot vehicles in a variety of industrial and commercial environmnets. The objectives of the vision research were to develop dynamic vision systems capable of continuous, ongoing information integration in a changing environment dealing with a variety of scenes, objects and shapes with the capacity for recognizing and locating the objects and parts of a scene of interest and, if necessary, tracking objects and features of interest as they or the camera platform are moved. Further developments involve geometric techniques that can create models of the objects and environments and use these models to support high level systems for visual path planning, object acquisition and control of the visual processing.
A number of basic visual competences involving obstacle detection, free space determination, local navigation, global map making, and object recognition, location and acquisition were developed and demonstrated on vision and vehicle experimental platforms at 4 laboratory sites within the project. 2 of these were further developed to show the potential passive vision for enhancing the capabilities of mobile vehicles in teleguided operation and in autonomous systems. A third final demonstration was used to illustrate how different vision systems and modules could be integrated on a multiprocessor distibuted environment. The fourth platform was used to demonstrate the potential of 1 of the systems developed for operation in outdoor scenes.
The objectives of the vision research carried out were to:
- develop dynamic vision systems capable of continuous, ongoing information integration in a changing environment
- be able to deal with a variety of scenes, objects and shapes as appropriate for the task in hand
- develop vision systems capable of recognising and locating the objects and parts of a scene of interest for the task in hand and, if necessary, capable of tracking objects and features of interest as they or the camera platform are moved
- develop geometric techniques that, where necessary, can create models of the objects and environments of interest, and use these models to support high-level systems for visual path planning, object acquisition and control of the visual processing
- explore parallel implementations of the systems developed,
- carry out a series of experiments, tests and demonstrations to assess and display the performance of the systems developed.
Meeting these objectives required significant advances in the state of the art: in early vision and the use of stereo and motion, in the use and exploitation of predictive feed-forward techniques and dynamic vision, in the range and type of models that can be utilised in a vision system, in the design of vision system architectures and their control structures, and in the implementation of vision systems on multiprocessor environments.
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HA9 7PP Wembley
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