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.