About

Bernard Mettler is a leading researcher in autonomous systems, robotics, and human-machine interaction, with a focus on unmanned aerial vehicles (UAVs) and motion planning. His seminal 2009 survey on motion planning algorithms for autonomous UAV guidance has garnered over 750 citations, establishing a foundational framework for the field. Mettler’s early work on identification modeling and characteristics of miniature rotorcraft (377 citations) advanced the understanding of small-scale aerial vehicle dynamics, enabling more precise control and autonomy. He has also made significant contributions to trajectory planning under uncertainty, notably through his receding horizon approach with environment-based cost-to-go functions, which provides a robust method for real-time 3D navigation in dynamic environments. Beyond algorithms, Mettler investigates human performance in teleoperated search tasks, analyzing visuo-motor control and coordination to improve human-robot teaming for applications like search and rescue. His research bridges theory and practice, with support from agencies such as ONR and NSF, and his work on probabilistic search and human planning continues to shape the next generation of autonomous guidance systems.

Research Focus

Key Achievements

9
H-Index
14
Papers
1,453
Total Citations
104
Avg Citations/Paper
🏆 Most Cited Paper
A Survey of Motion Planning Algorithms from the Perspective of Autonomous UAV Guidance
751 citations · 2009
📈 Most Prolific Year: 2009 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Minnesota, Decision Systems (United States), International Computer Science Institute, Massachusetts Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago