Drones in Automated and Robotized Internal Logistics: A Review of Optimization and Control Techniques

Drones have emerged as powerful tools for automation, real-time monitoring, and data collection, and their use in logistics continues to expand. In internal logistics, covering warehousing, inventory management, and intra-logistics tasks, drones offer opportunities to improve operational efficiency, accuracy, and cost-effectiveness. Despite these advantages, deploying drones in enclosed and cluttered indoor environments without Global Positioning System (GPS) requires reliable control and mission-level optimization strategies. This paper reviews recent approaches to drone mission control and optimization for internal logistics applications over the past decade. Drone applications are organized into three categories: inventory management, surveillance and inspection, and intra-logistics operations. For each category, we discuss key challenges spanning mission-level decision problems such as task allocation and path planning, and execution-level requirements such as navigation, obstacle avoidance, and flight control. We compare classical, robust, and adaptive control methods with emerging learning-based approaches, highlighting their advantages, limitations, and implementation challenges. Finally, we identify open issues and outline research directions related to swarm coordination and human–drone interaction, which are important for scalable deployment in modern internal logistics environments.