SLIDER: Memory-Efficient Aerial Robot Search with Sliding Local Maps

Jul 14, 2026

Researchers have introduced SLIDER, a framework for aerial robots that enables efficient target search in large, unknown environments without relying on dense global maps. SLIDER combines a local sliding map with sparse global history, a novel observation quality evaluation, and incremental viewpoint clustering to improve real-time decision-making and reduce computational load. Simulations and real-world experiments show that SLIDER outperforms state-of-the-art methods in memory usage, decision latency, and search efficiency.

Why it matters: This approach could make aerial robots more practical for large-scale search tasks by improving efficiency and reducing hardware requirements.

Full story at: arXiv Robotics ↗