Alan Slatter

Papers

Total Citations

H-Index

About

Alan Slatter is a roboticist whose research focuses on extending the operational endurance of aerial robots through novel perching and energy management strategies. His most cited work, "Learning Tethered Perching for Aerial Robots" (2023, 16 citations), tackles a critical bottleneck in drone technology: limited battery life. Slatter’s major contribution lies in developing learning-based control algorithms that enable drones to autonomously perch on structures using tethers, allowing them to conserve power while maintaining a stable, elevated position for long-duration data collection. This approach moves beyond simple hovering, which drains batteries, toward energy-neutral observation. While his citation count is still growing, the work is notable for its practical, real-world application in infrastructure inspection and environmental monitoring, where persistent aerial presence is essential. Slatter’s research sits at the intersection of reinforcement learning, control theory, and field robotics, offering a promising path toward truly long-endurance autonomous flight without relying solely on heavier batteries.