Johann Laconte made his debut in research by interacting with the Northern Robotics Laboratory during his studies in computer engineering at Clermont Auvergne University, working on the modeling of lidar sensors. He got his Engineering degree from this university in 2018, along a Master’s degree in robotics. He completed his Ph.D. at Institut Pascal (France) and Laval University (Canada) in 2021 during which he participated in several robotic deployments in unstructured environments, including subarctic forests. This work was awarded the second prize for the best french Ph.D. thesis in robotics. After a six-month postdoc at the Northern Robotics Laboratory (Norlab), he continued his research at the University of Toronto in Mobile Robotics (ASRL).

Since October 2023, he is the recipient of a junior research chair in the robotics department of the French National Institute for Agriculture, Food and Environment (INRAE).

His research interests focus on mobile robotics and the interactions between the robot and deformable, ever-changing environments.

Education

• Postdoc (Robotics) - University of Toronto, 2023
• Postdoc (Field Robotics) - Université Laval, 2022
• Ph.D. in Robotics - Clermont Auvergne University, 2021
• M.Sc. in Robotics - Clermont Auvergne University, 2018
• Engineering Degree in Computer Science and Modeling - ISIMA, 2018

Scientific Services

• Co-organizer of the Field Robotics Workshop at ICRA 2024
• Associate Editor for IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
• Regular reviewer for international journals and conferences (e.g., ICRA, IROS, RA-L)

Resume

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Publications

1. Courcelle, C., Baril, D., Pomerleau, F., & Laconte, J. (2023). On the Importance of Quantifying Visibility for Autonomous Vehicles Under Extreme Precipitation. Towards Human-Vehicle Harmonization, 3, 239.
2. Vaidis, M., Dubois, W., Guénette, A., Laconte, J., Kubelka Vladimı́r, & Pomerleau, F. (2023). Extrinsic calibration for highly accurate trajectories reconstruction. 2023 IEEE International Conference on Robotics and Automation (ICRA), 4185–4192.
3. Yoon, D. J., Burnett, K., Laconte, J., Chen, Y., Vhavle, H., Kammel, S., Reuther, J., & Barfoot, T. D. (2023). Need for Speed: Fast Correspondence-Free Lidar Odometry Using Doppler Velocity. ArXiv Preprint ArXiv:2303.06511.
4. Randriamiarintsoa, E., Laconte, J., Thuilot, B., & Aufrère, R. (2023). Risk-Aware Navigation for Mobile Robots in Unknown 3D Environments. ArXiv Preprint ArXiv:2309.02939.
5. Laconte, J., Lisus, D., & Barfoot, T. D. (2023). Toward Certifying Maps for Safe Localization Under Adversarial Corruption. ArXiv Preprint ArXiv:2309.04251.
6. Lisus, D., Laconte, J., Burnett, K., & Barfoot, T. D. (2023). Pointing the Way: Refining Radar-Lidar Localization Using Learned ICP Weights. ArXiv Preprint ArXiv:2309.08731.
7. Deschênes, S.-P., Baril, D., Boxan, M., Laconte, J., Giguère, P., & Pomerleau, F. (2023). Saturation-Aware Angular Velocity Estimation: Extending the Robustness of SLAM to Aggressive Motions. ArXiv Preprint ArXiv:2310.07844.
8. Laconte, J., Randriamiarintsoa, E., Kasmi, A., Pomerleau, F., Chapuis, R., Debain, C., & Aufrère, R. (2021). Dynamic Lambda-Field: A Counterpart of the Bayesian Occupancy Grid for Risk Assessment in Dynamic Environments. 2021 International Conference on Intelligent Robots and Systems (IROS).
9. Morceaux, J., Laconte, J., Randriamiarintsoa, E., Morell, T., Malaterre, L., Denis, D., Aufrère, R., & Chapuis, R. (2021). Toward a Generalized Risk Assessment Method on Occupancy Grids. IROS 2021: Late Breaking Results.
10. Laconte, J., Kasmi, A., Pomerleau, F., Chapuis, R., Malaterre, L., Debain, C., & Aufrère, R. (2021). A novel occupancy mapping framework for risk-aware path planning in unstructured environments. Sensors, 21(22), 7562.
11. Baril, D., Deschênes, S.-P., Gamache, O., Vaidis, M., LaRocque, D., Laconte, J., Kubelka Vladimı́r, Giguère, P., & Pomerleau, F. (2021). Kilometer-scale autonomous navigation in subarctic forests: challenges and lessons learned. ArXiv Preprint ArXiv:2111.13981.
12. Laconte, J., Kasmi, A., Aufrère, R., Vaidis, M., & Chapuis, R. (2021). A survey of localization methods for autonomous vehicles in highway scenarios. Sensors, 22(1), 247.
13. Laconte, J. (2021). Lambda-Field: a novel framework for risk assessment in occupancy grids [PhD thesis]. Université Clermont Auvergne.
14. Baril, D., Grondin, V., Deschênes, S.-P., Laconte, J., Vaidis, M., Kubelka Vladimı́r, Gallant, A., Giguere, P., & Pomerleau, F. (2020). Evaluation of skid-steering kinematic models for subarctic environments. 2020 17th Conference on Computer and Robot Vision (CRV), 198–205.
15. Kasmi, A., Laconte, J., Aufrère, R., Denis, D., & Chapuis, R. (2020). End-to-end probabilistic ego-vehicle localization framework. IEEE Transactions on Intelligent Vehicles, 6(1), 146–158.
16. Labussière, M., Laconte, J., & Pomerleau, F. (2020). Geometry preserving sampling method based on spectral decomposition for large-scale environments. Frontiers in Robotics and AI, 7, 572054.
17. Kasmi, A., Laconte, J., Aufrère, R., Theodose, R., Denis, D., & Chapuis, R. (2020). An information driven approach for ego-lane detection using Lidar and OpenStreetMap. 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), 522–528.
18. Vaidis, M., Laconte, J., Kubelka Vladimı́r, & Pomerleau, F. (2020). Improving the Iterative Closest Point Algorithm using Lie Algebra. IROS 2020 Workshop: Bringing Geometric Methods to Robot Learning, Optimization and Control.
19. Laconte, J., Deschênes, S.-P., Labussière, M., & Pomerleau, F. (2019). Lidar measurement bias estimation via return waveform modelling in a context of 3D mapping. 2019 International Conference on Robotics and Automation (ICRA), 8100–8106.
20. Laconte, J., Debain, C., Chapuis, R., Pomerleau, F., & Aufrère, R. (2019). Lambda-Field: A Continuous Counterpart of the Bayesian Occupancy Grid for Risk Assessment. 2019 International Conference on Intelligent Robots and Systems (IROS), 167–172.