Dylan Taylor

United States Military Academy

Papers

1

Total Citations

10

H-Index

1

About

Dylan Taylor is a robotics researcher whose work centers on autonomous aerial vehicle control, perception-guided navigation, and safe landing in unstructured environments. His most notable contribution is the development of a quadrotor system capable of autonomously landing on inclined surfaces up to 40°, a breakthrough designed for emergency scenarios where only sloped terrain is available. This work, published in 2021 and garnering 10 citations, introduces perception-guided active asymmetric skids that enable the drone to dynamically adjust its landing gear based on real-time surface analysis. Taylor’s research addresses a critical gap in drone safety and operational robustness, pushing the boundaries of what autonomous aerial vehicles can achieve in challenging, real-world conditions. By integrating advanced computer vision with adaptive mechanical design, his approach has implications for search-and-rescue, disaster response, and military logistics. Though early in his career, Taylor’s innovative solution to a pressing problem in autonomous flight demonstrates his potential to shape the future of resilient drone systems, making his work essential reading for researchers in field robotics and aerial autonomy.

Research Focus

Key Achievements

1
H-Index
1
Papers
10
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Autonomous Quadrotor Landing on Inclined Surfaces Using Perception-Guided Active Asymmetric Skids
10 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: United States Military Academy

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago