Johann Laconte

Johann Laconte

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

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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.

Education

  • 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

Publications

Conference Articles

  1. Labussière, M., Laconte, J., & Pomerleau, F. (2019). Geometry Preserving Sampling Method based on Spectral Decomposition for 3D Registration. In preprint, submitted to ICRA 2019.
  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 preprint, submitted to ICRA 2019.