Shows real-time UAV adaptation enhances heliostat calibration, suggesting improved field operations.
Unmanned aerial vehicle (UAV)-based methods are a promising option for heliostat calibration. However, existing approaches require prior knowledge of the heliostat orientation and rely on predefined flight paths, which can be difficult to determine when the assumed orientations are uncertain. Small orientation errors necessitate redundant flight segments to reliably capture the measurement signal, while largely misaligned heliostats cannot be measured altogether. This raises the question of whether real-time data processing can enable the dynamic adaptation of UAV flight paths. To address this, we present a novel method for the airborne real-time solar concentrator orientation estimation for heliostat fine calibration, termed ARTSCORE-F. Building on the HelioPoint measurement principle, the method introduces a closed-loop controller that incorporates the currently observed reflection signal as feedback. For the first time, a heliostat fine calibration point can be acquired autonomously without requiring previous calibration or accurate a priori orientation knowledge. The feedback loop actively guides the reflection signal toward defined locations on the concentrator surface while simultaneously controlling the UAV–concentrator distance, allowing online adaptation of the flight path to the actual measurement situation and avoiding redundant measurements. A dedicated simulation environment is used to systematically evaluate the method across varying system configurations and operating conditions. For an exemplary concentrator at the Solar Tower Jülich, the proposed method prepares a final surface scan within approximately one minute, even for arbitrary initial orientations. The method is applicable in tracking heliostat fields and enables targeted recalibration of individual heliostats without interrupting field operation.
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Schnerring et al. (2026) studied this question.
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