Johann Laconte

Johann Laconte

Started on

Expertise: Lidar modeling, ICP, Iterative Closest Point, registration, traversability

Follow me:
Google Scholar Google Scholar
Research Gate Research Gate
Linkedin Linkedin
Mendeley Mendeley

Johann Laconte is currently a Ph.D student in robotics at Institut Pascal, France. He got an Engineering degree in computer sciences and modelisation from ISIMA (Institut Supérieur d’Informatique, de Modélisation et de leurs Applications) as well as a Master’s degree in Robotics from Université d’Auvergne, France, in 2018. He did an internship at Thales, during which he participated in the development of LIDAR SLAM algorithm. He also did an research internship at Norlab, working on the characterization of LIDAR’s bias. His current works are about traversability and risk assessments in dynamic environments.


  • M.Sc. in Robotics and Artificial Perception - University of Auvergne (UCA), 2018
  • Engineering degree in computer Sciences and Modelisation - Institut Supérieur d’Informatique, de Modélisation et de leurs Applications (ISIMA), 2018


Conference Articles

  1. Laconte, J., Debain, C., Chapuis, R., Pomerleau, F., & Aufrere, R. (2019). Lambda-Field: A Continuous Counterpart of the Bayesian Occupancy Grid for Risk Assessment. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS). Bibtex source
  2. Laconte, J., Deschênes, S.-P., Labussière, M., & Pomerleau, F. (2019). Lidar Measurement Bias Estimation via Return Waveform Modelling in a Context of 3D Mapping. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). PDF Bibtex source


  1. Labussière, M., Laconte, J., & Pomerleau, F. (2019). Geometry Preserving Sampling Method based on Spectral Decomposition for 3D Registration. arXiv:1810.01666. Bibtex source