Simulation and experimental study demonstrates a 67% reduction in trajectory tracking error in an over-actuated water-jet UAV, highlighting the viability of autonomous facade maintenance.
Uncrewed aerial vehicles (UAVs) represent a promising alternative for building facade cleaning, improving efficiency while reducing the risks associated with working at height. However, such operations are particularly challenging due to the reaction forces generated by fluid discharge, which can compromise UAV stability and reduce cleaning accuracy. To mitigate this issue, this work proposes an integrated methodology for the preliminary assessment of UAV-based water-jet facade cleaning operations. First, a Computational Fluid Dynamics (CFD) model is developed to characterize jet-induced forces as a function of nozzle parameters and stand-off distance. The proposed force estimation model is evaluated experimentally at one low-pressure operating condition through flight tests using a commercial water-jet cleaning system. These disturbance forces are then incorporated into an over-actuated UAV dynamic model, together with a disturbance-aware compensation strategy, enabling the evaluation of vehicle stability and trajectory tracking under the simulated operating conditions. In parallel, a trajectory generation and operational planning framework is proposed, allowing systematic coverage of facades while maintaining the prescribed stand-off distances. The proposed framework is evaluated through nine simulation scenarios considering different flow rates and disturbance levels. The results demonstrate accurate trajectory tracking, with RMS errors below 3.4 cm across all cases, while the proposed disturbance compensation strategy reduces the RMS tracking error by approximately 67% compared with a non-compensated configuration. The results highlight the potential of UAV-based water-jet systems for autonomous and efficient facade maintenance, while also illustrating the importance of accounting for jet-induced disturbances in the control design.
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Martínez-Alonso et al. (2026) studied this question.
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