Industries using a CAD-system to design parts or working areas need a means of feedback to enable a comparison of designed and manufactured structures. Using vision, based on the CAD information, is an effective tool to establish this link. For example, the autonomy of a robotic vehicle is needed in several applications in building and inspecting of large structures, such as ship bodies. The navigation of a walking robot will be demonstrated using this vision tool. Furthermore, the vision tool can be used for the task of dimensional measurements of parts. The project costs over a period of two years are 1125 kECU including 750 kECU funding from the CEC.
This project develops a vision system that finds and measures the location of 3D structures with respect to a CAD-model. The integration of a CAD-model to visual measurement and direct feedback of measurement results is a key aspect. The objective is to render visual processing robust to deviations in parts and environmental conditions. To achieve this goal a technique is developed that integrates different cues of images to obtain confidence of the measurement result.
Reliability is tackled by developing a theory of robust visual recognition by integrating redundant low level image cues and sparse high level object knowledge. Image cues and object knowledge are exploited and integrated both at a local and global level. For the extraction of basic visual cues independent and complimentary modules are envisaged. The modularity of the toolbox is the basis for integrating the acquisition of visual information with tools of the control and engineering process.
The project focuses on using the vision system for guiding a robotic vehicle to enable it to navigate and position itself in order to deliver work packages for inspection, welding and other tasks for the structure/body of a large vessel during production. The final demonstration will see the walking robot enter and climb the vessel structure..
The ROBVISION project will achieve the following results:
The potential uses for such a tool are quite diverse. The principal capability is to use a CAD-model to find features in images and to return the position and orientation measured back into the CAD-model.