Autonomous Payload Delivery: A Sequential Approach Using Single and Heterogeneous Drones

Heterogeneous drones for payload delivery leverage the distinct strengths of each drone type, enabling the use of heterogeneous drones for payload delivery, which is essential because it controls the unique strengths of each drone. It allows efficient handling of complex tasks that would be challenging for homogeneous drones. The use of heterogeneous drones allows for optimized resource allocation, enhanced stability, and increased payload capacity, making it possible to facilitate the precise transport of heavier or irregularly shaped loads with precision and adaptability. The growing need for autonomous payload delivery in dynamic environments forced us to develop robust control mechanisms for multiple heterogeneous drone systems. To address these challenges, we propose a multiphase control strategy that integrates robust and adaptive control techniques for single and cooperative drone operation, ensuring precise trajectory tracking and payload stability. This proposed work introduces a novel approach to autonomous payload delivery for single and multiple heterogeneous drones. For single-drone operations, a sliding mode controller (SMC) enables a drone to track a predefined trajectory, autonomously identify the payload′s center of mass (CoM), securely attach to it, lift, and deliver it to the target location. To handle heavier or more complex payloads requiring enhanced stability and coordination, we extend the proposed approach to cooperative transport using multiple heterogeneous drones, introducing increased complexity due to their differing dynamics and synchronization requirements. A distributed sliding mode controller (DSMC) strategy is developed to synchronize two heterogeneous drones with distinct thrust and payload capacities, ensuring stable lifting and precise trajectory tracking. Simulation results demonstrate that the SMC and DSMC achieve superior tracking accuracy, payload stability, and energy efficiency compared to homogeneous drone systems, enabling robust autonomous delivery in dynamic and complex environments.