<p>This survey presents a systematic analysis of recent advancements in autonomous unmanned aerial vehicles (UAVs), focusing on their navigation and control systems. The paper provides a critical overview of the key technologies in navigation and control systems that enhance UAV autonomy. It focuses on three main aspects: perception and state estimation (navigation, target tracking, GNSS-denied environments); path planning (obstacle avoidance, autonomous takeoff/landing); and operating conditions (wind disturbances, night efficiency). Our findings highlight that critical developments, including vision-based and hybrid navigation frameworks, reinforcement learning methods, and energy-aware planning, are significantly advancing UAV capabilities, especially in terms of navigation in GPS-denied environments, path efficiency, energy optimization, and multi-UAV communication. The contributions of this survey include a unified taxonomy linking the perception, control, and energy subsystems, the identification of essential open research gaps, and the provision of structured recommendations to guide future research. Furthermore, by synthesizing a wide range of technologies, the survey identifies current challenges and points to future research opportunities for achieving safe, efficient, and fully autonomous UAV operation.</p>