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Biography

Cyril Joly is a researcher specializing in the fields of mobile robotics, localization, and perception for autonomous systems. His work focuses on developing innovative methods for semantic LiDAR segmentation, sensor fusion (vision, Wi-Fi, magnetometers, inertial sensors), and the optimization of real-time localization algorithms, particularly in constrained or dynamic environments. His research addresses challenges such as sensor calibration, magnetic field modeling for indoor navigation, and the integration of multi-source data to improve the robustness of SLAM (Simultaneous Localization and Mapping) systems. His contributions include hybrid approaches combining deep learning, probabilistic filtering, and geometric methods, with a particular focus on computational efficiency and adaptability to embedded platforms.

Publication(s)

Teaching

Course 1, 2, or 3 - (PI IDS)

Course Director

Touchdown/Touchdown (Pass Interference IDS)

Course Director

Project (PI IDS)

Course Director

PhD supervision

  • 2025 Simultaneous Localization and Mapping with Traversability Information in Unstructured Environments CALZAS Julien
  • 2024 Incremental 3D reconstruction based on a neural representation DAIRE Nicolas
  • 2022 Magneto-visual-inertial fusion for indoor localization ABDUL RAOUF IAD
  • 2022 Deep neural networks for semantic segmentation of 3D point clouds adapted to embedded architectures for autonomous mobile and robotic systems ABOU HAIDAR Samir
  • 2020 Indoor localization by magneto-visual-inertial SLAM COULIN Jade
  • 2020 High-resolution automotive radar data processing using deep learning techniques inspired by computer vision ZHOU ZHUYUN
  • 2017 SLAM and sensor fusion for autonomous vehicles ANDRADE VALENTE DA SILVA Michelle
  • 2016 Localization of a humanoid robot in unconstrained indoor environments NOWAKOWSKI Mathieu