Helen Oleynikova

ETH Zurich, Microsoft (Switzerland)

Papers

20

Total Citations

1,844

H-Index

14

About

Helen Oleynikova is a robotics researcher whose work spans autonomous exploration, motion planning, and human-robot interaction, with a particular focus on enabling aerial robots to operate safely and intelligently in unknown environments. She is perhaps best known for her highly influential 2016 paper introducing the Receding Horizon "Next-Best-View" Planner, a landmark contribution to autonomous 3D exploration that has garnered over 600 citations and become a foundational reference in robotic path planning. Her concurrent work on continuous-time trajectory optimization for UAV replanning — cited over 370 times across related publications — demonstrated practical methods for real-time collision avoidance in unstructured spaces. Oleynikova has also made significant contributions to map representation, advocating for signed distance fields as a unified framework for both mapping and planning. Her later research expanded into parallel GPU-based motion generation for robotic manipulators with CuRobo, and into mixed reality interfaces that bring spatial computing and robotics together for more intuitive human-robot interaction. Spanning embedded hardware, aerial autonomy, and manipulation, her body of work reflects a rare breadth, consistently bridging theoretical rigor with real-world robotic deployment.

Research Focus

Key Achievements

14
H-Index
20
Papers
1,844
Total Citations
92
Avg Citations/Paper
🏆 Most Cited Paper
Receding Horizon "Next-Best-View" Planner for 3D Exploration
601 citations · 2016
📈 Most Prolific Year: 2016 (6 Papers)
🤝 Key Collaborators: 57
🏛 Institutions: ETH Zurich, Microsoft (Switzerland)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago