Michael Pantic
Papers
13
Total Citations
421
H-Index
7
About
Michael Pantic is a robotics researcher whose work spans autonomous aerial systems, motion planning, and real-world robotic applications. He is best known for his influential 2020 paper on sampling-based informative path planning for unknown environments, which has garnered nearly 300 citations and addressed critical challenges in online robot autonomy, particularly the problem of local minima in trajectory optimization. His research extends into surface-interaction planning, where his Riemannian Motion Policy frameworks enable micro aerial vehicles (MAVs) to navigate complex 3D environments and interact physically with surfaces at remarkable computational speeds. Pantic has also made notable contributions to applied robotics, including autonomous non-destructive testing of reinforced concrete infrastructure using UAVs, precise aerial marking for construction tasks, and safe planetary landing site detection. His involvement in the ETH Zurich team at the Mohamed Bin Zayed International Robotics Challenge highlights his commitment to deploying robust systems in competitive, real-world conditions. Spanning perception, planning, and physical interaction, Pantic's body of work represents a cohesive effort to bridge theoretical advances in autonomous navigation with practical, safety-critical applications across inspection, construction, and exploration domains.
Research Focus
Key Achievements
Top Papers
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- 3TERESA: a socially intelligent semi-autonomous telepresence system21 citations · 2015
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- 8The ETH‐MAV Team in the MBZ International Robotics Challenge7 citations · 2018
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