Conflict-Predictive Variable Horizons in Multi-Drone Distributed Model Predictive Control
In distributed model predictive control for multi-drone collision avoidance, a fixed prediction horizon forces a compromise: a short horizon is inexpensive but reacts late to approaching neighbors, whereas a long one anticipates conflicts at a per-step cost that grows superlinearly with its length. We propose a conflict-predictive variable horizon that each drone sets locally, leaving the distributed model predictive control itself unchanged. From a short history of observed positions, a drone extrapolates the flight lines of its neighbors, tests each against its own using confidence funnels that narrow with prediction range, and obtains each time to conflict in closed form. The horizon i...
| Authors | Linda Mümken, Michael Schwung, Stefan Lier et al. |
|---|---|
| Primary category | cs.RO |
| Published | 7 September 2026 |
| Last updated at source | 7 September 2026 |
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