Papers
4
Total Citations
43
H-Index
4
About
Martin Jacquet is a leading researcher at the intersection of aerial robotics, human-robot interaction, and autonomous navigation. His work focuses on enabling drones to perform complex physical tasks alongside humans, with a particular emphasis on safety and ergonomics. Jacquet’s major contributions include the development of a Nonlinear Model Predictive Control (NMPC) for human-robot handovers, allowing aerial robots to autonomously deliver objects to human coworkers in a safe and ergonomic manner—a key step toward practical collaborative drones. He has also pioneered the use of Neural Control Barrier Functions for safe robot navigation in unknown environments, a data-driven approach that ensures safety even when the surroundings are not pre-mapped. With his most-cited works accumulating over 40 citations, Jacquet’s impact is evident in the growing field of physically interactive aerial systems. His general control architecture for visual servoing and physical interaction tasks further demonstrates his ability to unify perception and manipulation, making his work foundational for future applications in logistics, manufacturing, and search-and-rescue.
Research Focus
Key Achievements
Top Papers
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- 2Neural Control Barrier Functions for Safe Navigation13 citations · 2024
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