Abstract

Autonomous takeoff and landing (ATOL) remains one of the most challenging tasks for fixed-wing unmanned aerial vehicles (UAVs), particularly in environments where Global Navigation Satellite System (GNSS) signals are degraded or unavailable. This paper presents an LiDAR-assisted terrain-relative navigation framework for the autonomous takeoff and landing of a 5 kg fixed-wing UAV operating under degraded navigation conditions. The proposed architecture integrates a downward-facing LiDAR rangefinder with barometric altitude sensing, INS/GNSS navigation, optical-flow measurements, and airspeed information within a multi-sensor fusion and flight-control framework. The system combines a Pixhawk-based autopilot with a companion-computer architecture responsible for real-time sensor processing, altitude estimation, mission supervision, and MAVLink-based communication. A dedicated filtering strategy and sensor fusion approach enable reliable terrain-relative altitude estimation during critical low-altitude flight phases, while fault-tolerant command-management mechanisms improve operational robustness in the presence of temporary communication losses and sensor disturbances. The proposed framework was validated through Software-in-the-Loop (SITL), Hardware-in-the-Loop (HITL), and real-flight experiments. Experimental results demonstrated stable and repeatable autonomous landing performance. Comparative analyses showed that the LiDAR sensor provided the most accurate and responsive terrain-relative altitude measurements during takeoff, flare, and landing operations, particularly over irregular and vegetation-covered surfaces. In contrast, barometric sensing provided greater long-term stability during cruise flight, highlighting the importance of multi-sensor fusion for reliable altitude estimation throughout the mission profile. The results confirm that LiDAR-based terrain-relative sensing significantly improves autonomous takeoff and landing performance for fixed-wing UAVs operating in GNSS-degraded environments. The proposed architecture offers a practical and low-cost solution for the autonomous takeoff and landing of fixed-wing UAVs operating in GNSS-degraded environments while demonstrating the benefits of integrating LiDAR, inertial, barometric, and GNSS measurements within a unified multi-sensor autonomous flight framework.

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