Papers
10
Total Citations
252
H-Index
5
About
Turcan Tuna is a robotics researcher specializing in robust localization, LiDAR-based perception, and autonomous navigation in extreme and unstructured environments. His work sits at the intersection of state estimation, legged robotics, and real-world field deployment, addressing some of the most persistent challenges in reliable robot autonomy. Tuna is perhaps best known for developing X-ICP, a localizability-aware LiDAR registration framework that significantly improves the robustness of the Iterative Closest Point algorithm in geometrically degenerate environments — a paper that has garnered over 111 citations since 2023. His complementary work on degeneracy-aware point cloud registration further advances this line of inquiry with rigorous field analysis. He also contributed to the widely cited scientific exploration of planetary analog environments using teams of legged robots (104 citations), demonstrating the real-world applicability of his ideas in high-stakes settings. Beyond localization, Tuna has broadened his scope to continuous-time state estimation, autonomous forest inventory, LiDAR place recognition in natural environments, and novel robotic platforms like LEVA, a high-mobility logistics vehicle. His research consistently bridges algorithmic innovation with demanding physical deployments, making him an increasingly influential voice in field robotics and autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 3Continuous-Time State Estimation Methods in Robotics: A Survey11 citations · 2025
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- 6LEVA: A High-Mobility Logistic Vehicle with Legged Suspension4 citations · 2025
- 7Continuous-Time State Estimation Methods in Robotics: A Survey4 citations · 2024
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