Autonomous landing of a UAV for inductive charging using onboard sensing
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Date
2026-07-06
Authors
Διαβολίτσης, Παναγιώτης Ελευθέριος
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Abstract
In the modern era, technological advancement in Unmanned Aerial Vehicles (UAVs) has catalyzed a paradigm shift in applications ranging from industrial surveillance to autonomous logistics. Rotary-wing UAVs are uniquely suited for these tasks, yet theiroperations are fundamentally constrained by limited energy storage. Wireless Power Transmission (WPT) emerges as a transformative solution; however, its efficacy relies on precise spatial alignment between the UAV and the charging pad. Addressing this requirement, this thesis presents an integrated framework designed to develop and evaluate high-precision landing control architectures.The core of our research involved the design of a modular landing pipeline. During system integration, we encountered hardware-specific communication bottlenecks and latency issues that compromised the determinism of the control loop. To address these, we implemented a hybrid framework that bridges the gap between high-precision external localization and modular control design. By leveraging the Lighthouse Positioning System to provide stable ground-truth data, we successfully isolated and validated the performance of advanced control laws, specifically Proportional-Derivative (PD) feedback, within a deterministic environment.The system was evaluated using the Bitcraze Crazyflie 2.1 platform. While the visionbased feature extraction was prototyped using the AI-deck, our experimental results primarily validate the robustness of the PD control architecture and the precision of the landing maneuvers under controlled localization. This research establishes a reproducible methodology for control design in resource-constrained UAVs, emphasizing theimportance of deterministic feedback loops in precision navigation. In conclusion, this work provides a comprehensive framework for autonomous landing, demonstrating that modular, control-centric architectures can effectively serve as a reliable foundation for future advancements in dynamic platform landing and sustained, zero-human-intervention flight.
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Keywords
Drone, Vision, Control, Landing