Pierre Dellenbach

Papers

Total Citations

253

H-Index

About

Pierre Dellenbach is a leading researcher in robotics and autonomous systems, with a primary focus on LiDAR-based localization, mapping, and odometry. His most impactful contribution is the development of **CT-ICP (Continuous-Time Iterative Closest Point)**, a real-time elastic LiDAR odometry method introduced in 2022. This work, which has garnered over 250 citations, addresses a critical challenge in autonomous navigation: building precise maps of dynamic environments using multi-beam LiDAR sensors. By enabling continuous-time trajectory estimation, CT-ICP significantly improves accuracy and robustness in real-time applications, particularly for autonomous cars. Dellenbach’s research bridges the gap between theoretical sensor fusion and practical deployment, making his methods widely adopted in both academic and industrial robotics. His work on loop closure further enhances long-term mapping reliability. Through CT-ICP, Dellenbach has established himself as a key figure in advancing LiDAR-only perception systems, with his contributions directly influencing the development of safer, more reliable autonomous vehicles.