Daniel Watman

UNSW Sydney

Papers

2

Total Citations

10

H-Index

2

About

Daniel Watman’s research bridges the frontiers of autonomous robotics and bio-inspired flight, with a focus on practical, real-world applications. In autonomous vehicle navigation, Watman developed a novel grid-based scan-to-map matching technique for map-based navigation, enabling a modified Toyota Prius to precisely control throttle, brake, and steering without human intervention. This work, cited 5 times, laid foundational methods for self-driving car localization in structured environments. In parallel, Watman conducted a seminal parametric study on flapping wing performance using a robotic testbed, exploring how passive wing dynamics affect propulsion efficiency for Micro Aerial Vehicles (MAVs). This 2009 study, also garnering 5 citations, provided critical insights into the aerodynamic trade-offs of flapping motion, informing the design of more agile, energy-efficient drones. While his citation counts reflect a focused, early-career impact, Watman’s contributions are notable for their dual-domain innovation—advancing both ground-based autonomy and aerial bio-robotics. His work demonstrates a rare ability to translate complex mechanical principles into functional prototypes, making him a researcher to watch at the intersection of robotics and fluid dynamics.

Research Focus

Key Achievements

2
H-Index
2
Papers
10
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Map-Based Navigation of an Autonomous Car Using Grid-Based Scan-to-Map Matching
5 citations · 2015
📈 Most Prolific Year: 2015 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: UNSW Sydney

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago