Distributed Model Predictive Control with Adaptive Safety Zones for Multi-Fleet Drone Operations
Autonomous drone swarms in space-constrained environments such as warehouses, inspection corridors, and urban delivery routes must share limited airspace safely at high vehicle density. Existing approaches rely on fixed safety zones sized for worst-case velocity, which wastes airspace in congested scenarios. We replace the fixed radius with an adaptive, speed-dependent safety sphere whose size scales with braking distance: tight at low speeds, expanded at high speeds. We develop both a centralized model predictive control (MPC) formulation and a distributed MPC (DMPC) in which each drone optimizes locally from detected neighbors, accommodating mixed fleets with non-cooperative agents. We ...
| Authors | Linda Mümken, Diyar Altinses, Michael Schwung et al. |
|---|---|
| Primary category | eess.SY |
| Published | 8 June 2026 |
| Last updated at source | 8 June 2026 |
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