Optimal camera placement to measure distances regarding static and dynamic obstacles
In modern production facilities industrial robots and humans are supposed to share a common working area. To avoid collisions, the distances between objects need to be measured conservatively, which can be done by a camera network. To estimate these distances, unmodelled objects, e.g. an interacting human, need to be modelled and distinguished from pre-modelled objects, like workbenches or robots, by image processing such as the background subtraction method. The quality of such an approach massively depends on the position and orientation of each camera. Of particular interest in this context is the error minimisation of the above mentioned distance determined by image processing. Here, we formulate this minimisation as an abstract optimisation problem. Moreover, we state various aspects on the implementation, e.g. reasons for the selection of a suitable optimisation method, analyse the complexity of the proposed method and present a basic version used for extensive experiments.
camera placement dynamic obstacles obstacles camera network position and orientation error minimisation optimisation close range photogrammetry distance measurement optimal placement static obstacles optimal image processing sensor network occlusions