Robust Energy-Aware Routing for Air-Ground Cooperative Multi-UAV Delivery in Wind-Uncertain Environments

A research team from multiple institutions, led by Tianshun Li, has published a new paper titled 'Robust Energy-Aware Routing for Air-Ground Cooperative Multi-UAV Delivery in Wind-Uncertain Environments.' The core innovation is Battery-Efficient Routing (BER), an online, risk-sensitive planning framework designed specifically for wind-sensitive, truck-assisted drone delivery systems. The problem is fundamentally re-framed as routing on a time-dependent energy graph, where edge costs evolve based on real-time, wind-induced aerodynamic effects. Unlike most existing approaches that assume static or deterministic energy models, BER continuously evaluates a drone's feasibility to return to its truck base, dynamically balancing immediate energy expenditure with an uncertainty-aware assessment of risk.

The approach is embedded within a hierarchical aerial-ground delivery architecture that combines task allocation, routing, and decentralized trajectory execution. The researchers validated BER through extensive simulations using synthetic energy-requirement graphs generated in Unreal Engine environments and quasi-real wind logs. Their results demonstrate that BER significantly improves mission success rates and reduces wind-induced failures when compared to both static planning and greedy baseline algorithms. This work underscores a critical shift in logistics robotics: for reliable autonomous delivery, planning must integrate real-time environmental awareness and proactive energy budgeting, moving beyond simplistic, pre-computed routes.