<p>Free space path finding remains the most critical challenge to efficient and safe autonomous drone operations. This paper presents an advanced approach toward free space pathfinding. Improved sensing technologies are combined with cultured algorithms for drone-efficient navigation. This AMFPO (Adaptive Multi-sensor Fusion and Path Optimization) technique fuses real-time data from multiple sensors, including location sensors to build a comprehensive environmental model. It enables the autonomous drone to identify dynamically the best paths and navigate them while avoiding obstacles. Extensive simulations and real-world experiments validate our approach with significantly improved path accuracy, obstacle avoidance, and flight efficiency. The paper contributes to the growth of autonomous drone technology with a robust framework for free space navigation applicable in logistics to emergency response industries by the AMFPO algorithm. The AMFPO architecture fully exploits each algorithm’s unique strength and therefore improves drone performance regarding precision in data collection, processing speed, and navigation efficiency. The effectiveness of developing such an efficient free space path detecting strategy strengthens the capabilities of autonomous drones and opens vast, novel standpoints for their application in complex and unpredictable environments.</p>