Daniil Lisus
Papers
1
Total Citations
3
H-Index
1
About
Daniil Lisus is a researcher focused on the safety and reliability of autonomous vehicle localization, particularly in challenging, real-world environments. His work addresses the critical challenge of certifying map-based localization under adverse conditions, where sensor data may be corrupted. In his most-cited paper, "Toward Certifying Maps for Safe Registration-Based Localization Under Adverse Conditions" (2023), Lisus proposes a novel framework to model the resilience of the Iterative Closest Point (ICP) algorithm against measurement corruption. This contribution is foundational for developing formal safety guarantees in autonomous navigation, enabling robots to operate confidently even when sensor inputs are unreliable. With 3 citations to date, his research is gaining traction among robotics and safety-critical systems communities. Lisus’s work bridges the gap between theoretical certification and practical deployment, offering a pathway to more trustworthy autonomous systems. His insights are particularly valuable for students and engineers seeking to understand how to rigorously assess localization robustness, making him a promising voice in the field of safe autonomy.
Research Focus
Key Achievements
Top Papers
- 1