Jean‐Emmanuel Deschaud

Centre de Robotique, ParisTech, Université Paris Sciences et Lettres, École Nationale Supérieure des Mines de Paris

Papers

Total Citations

300

H-Index

About

Jean-Emmanuel Deschaud is a leading researcher in robotics and autonomous systems, specializing in LiDAR-based perception, state estimation, and simultaneous localization and mapping (SLAM). His most impactful contribution is **CT-ICP**, a real-time elastic LiDAR odometry method that achieves loop closure with exceptional precision, garnering **253 citations** and setting a new standard for localization in autonomous driving. He also developed **IMLS-SLAM**, a scan-to-model matching approach that advances 3D mapping for depth sensors. Beyond terrestrial robotics, Deschaud has innovated in humanoid robot state estimation with a **multi-IMU proprioceptive estimator**, addressing the challenges of dynamic heel-toe walking gaits. His work on **Invariant Extended Kalman Filter-based SLAM** demonstrated robust scan matching for wheeled robots, while his recent exploration of **real-time LiDAR semantic segmentation** pushes the boundaries of scene understanding for autonomous driving. With a career marked by high-impact, real-time solutions, Deschaud’s research bridges theory and practical deployment, making him a pivotal figure in advancing robotic perception and navigation.