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The 4-meter Multi-Object Spectroscopic Telescope (4MOST) instrument uses 2436 individually positioned optical fibres to couple the light of targets into its spectrographs. The Fibre Target Alignment (FTA) software controls all aspects of the 4MOST instrument that are involved to position the 2448 spines of the AESOP positioner to their target locations closer than 10µm RMS, within 90 seconds. The AESOP fibre positioner provides a HTML interface which is used by the FTA software to command spine movements. The metrology system consists of four cameras, and a sophisticated software package to measure the location of fibres, which are moved by the AESOP spines. Spines reach their target typically after six to eight iterative movements, which are interlaced with metrology frames. The metrology software is capable of taking 4 images simultaneously, and reconstructing fibre positions to within 3μm RMS within five seconds. We present the FTA control software architecture, the interaction of sub-components and the different operation modes of the system. Especially the concurrent and simultaneous control of four metrology camera processes. Due to the complexity of the system, comprehensive debugging and visualization tools have been developed which allow a detailed understanding and interaction of the entire system. The graphical tool provides feedback for each individual camera stream and their combined result. It provides statistics and tools to manipulate individual spines, especially to recover them in case of entanglement. To develop the control software, a full end-to-end simulator has been created, which closes the loop between metrology image simulation, simulated fibre positioning and all control aspects in between. The metrology system uses the current spine position as presented by the AESOP positioner to render metrology camera images. Analysis and downstream computation is identical to the live software. When commanded to move spines, The AESOP simulator executes the identical steps to move spines, except sending electrical signals. After which it returns the expected spine positions after their move, which is taken as input for the next FTA iteration.
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Winkler et al. (2024) studied this question.
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