Smart Hexacopter For Payload Delivery

Abstract

The advancement of multirotor unmanned aerial vehicles (UAVs) has enabled their deployment in logistics, emergency response, surveillance, and industrial automation applications. Heavy-lift UAV platforms, particularly hexacopters, provide enhanced thrust redundancy and improved payload stability compared to quadrotor systems [1], [5]. However, increasing payload mass significantly affects thrust-to-weight ratio, energy consumption, and flight endurance due to nonlinear propulsion dynamics and Li-Po battery discharge characteristics [6], [17], [20].

This research presents the design, modeling, implementation, and experimental validation of an AI-enabled heavy-lift hexacopter capable of transporting payloads up to 2.5 kg. The proposed system integrates nonlinear multirotor dynamic modeling [9], [10], adaptive altitude stabilization [2], regression-based energy prediction [18], and PX4-based flight control architecture [14]. Experimental results demonstrate endurance reduction from 19 minutes (no payload) to 9 minutes (2.5 kg payload), while current consumption increases from 18 A to 47 A. The AI prediction model achieved 95% endurance estimation accuracy. The proposed architecture demonstrates scalability for logistics and medium-payload aerial transport systems [4], [19].