A Dataset of Distributed Operational States and Resource Allocation for Urban Low-Altitude Logistics Drone Swarms

It comprehensively covers complete flight state records of multiple drones over continuous time periods, involving 10 logistics drones and 100 logistics tasks, cumulatively generating 1.0486 million high-precision operational state records. The dataset fully records multi-dimensional dynamic information during the distributed operation of the drone swarm, providing a complete data foundation for research on drone swarm operational state analysis, resource allocation optimization, and task scheduling strategies.The dataset covers the complete task cycle of drones from takeoff, cruise, and maneuvering to landing, and includes various typical operational scenarios such as formation keeping, dynamic obstacle avoidance, path re-planning, and cooperative resource gaming phases.

Data were collected at millisecond-level frequency, preserving typical disturbance characteristics of the urban low-altitude environment (such as wind shear, signal attenuation caused by building occlusion), providing a realistic, fine-grained data foundation for the validation and optimization of distributed control algorithms, resource allocation models, and their coupling mechanisms.Stored in structured tabular format accompanied by detailed metadata descriptions and usage examples, providing an open and reliable data resource for interdisciplinary research in drone swarms, distributed systems, urban logistics, etc.This dataset is stored in a structured tabular format, accompanied by detailed metadata descriptions and usage examples, aiming to provide an open and reliable data resource for interdisciplinary research in drone swarms, distributed systems, urban logistics, and related fields.