Ivan Penskiy

University of Maryland, College Park

Papers

2

Total Citations

32

H-Index

2

About

Ivan Penskiy is a roboticist whose work bridges the gap between bio-inspired mechanics and autonomous navigation. His research focuses on miniature legged locomotion and multi-modal perception for outdoor robotics. In his most cited work, “Using an inertial tail for rapid turns on a miniature legged robot” (2013, 30 citations), Penskiy demonstrated how a dynamic tail—inspired by animals like geckos and cheetahs—can enable underactuated robots to execute rapid, agile turns. This contribution provided a foundational principle for enhancing maneuverability in small-scale robots without adding complex actuation. More recently, Penskiy co-authored “GND: Global Navigation Dataset With Multi-Modal Perception and Multi-Category Traversability in Outdoor Campus Environments” (2025), which addresses the challenge of navigating large-scale, unstructured outdoor spaces. By integrating LiDAR, cameras, and terrain semantics, this dataset supports the development of robots that can reason about geometry, environment, and traversability simultaneously. Penskiy’s work is notable for combining elegant mechanical design with practical perception systems, advancing both the agility and autonomy of field robots.

Research Focus

Key Achievements

2
H-Index
2
Papers
32
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Using an inertial tail for rapid turns on a miniature legged robot
30 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University of Maryland, College Park

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago