Featured Publications

October 23, 2020

Improving the Iterative Closest Point Algorithm using Lie Algebra

Mapping algorithms that rely on registering point clouds inevitably suffer from local drift, both in localization and in the built map. Applications that req...

September 30, 2020

Geometry Preserving Sampling Method based on Spectral Decomposition for Large-scale Environments

In the context of 3D mapping, larger and larger point clouds are acquired with lidar sensors. Although pleasing to the eye, dense maps are not necessarily ta...

May 13, 2020

Evaluation of Skid-Steering Kinematic Models for Subarctic Environments

In subarctic and arctic areas, large and heavy skid-steered robots are preferred for their robustness and ability to operate on difficult terrain. State esti...

September 13, 2019

Large-scale 3D Mapping of Subarctic Forests

The ability to map challenging subarctic environments opens new horizons for robotic deployments in industries such as forestry, surveillance, and open-pit m...

September 02, 2019

Lambda-Field: A Continuous Counterpart of the Bayesian Occupancy Grid for Risk Assessment

In a context of autonomous robots, one of the most important tasks is to ensure the safety of the robot and its surrounding. The risk of navigation is usuall...

May 27, 2019

Lidar Measurement Bias Estimation via Return Waveform Modelling in a Context of 3D Mapping

In a context of 3D mapping, it is very important to obtain accurate measurements from sensors. In particular, LIDAR measurements are typically treated as a z...

May 09, 2019

Predicting GNSS satellite visibility from dense point clouds

To help future mobile agents plan their movement in harsh environments,a predictive model has been designed to determine what areas would be favorable for Gl...

April 17, 2019

Automatic 3D Mapping for Tree Diameter Measurements in Inventory Operations

Forestry is a major industry in many parts of the world. It relies on forest inventory, which consists of measuring tree attributes. We propose to use 3D m...

February 14, 2019

Survey on UAV, lidar and underground mapping

This survey presents an overall view of lidar (Light Detection And Ranging) used on UAV (Unmanned Aerial Vehicle) and their project.

May 12, 2018

Learning a Bias Correction for Lidar-only Motion Estimation

This paper presents a novel technique to correct for bias in a classical estimator using a learning approach. We apply a learned bias correction to a lidar-o...

June 25, 2015

A Review of Point Cloud Registration Algorithms for Mobile Robotics

The topic of this review is geometric registration in robotics. Registration algorithms associate sets of data into a common coordinate system. They have b...

September 06, 2012

Challenging Data Sets for Point Cloud Registration Algorithms

This group of datasets was recorded with the aim to test point cloud registration algorithms in specific environments and conditions. Special care is taken ...

Exhaustive List

2021

1. Deschênes, S.-P., Baril, D., Kubelka, V., Giguère, P., & Pomerleau, F. (2021). Lidar Scan Registration Robust to Extreme Motions. 2021 18th Conference on Robots and Vision (CRV). [https://arxiv.org/abs/2105.01215](https://arxiv.org/abs/2105.01215) PDF Bibtex source

2020

1. Vaidis, M., Laconte, J., Kubelka, V., & Pomerleau, F. (2020). Improving the Iterative Closest Point Algorithm using Lie Algebra. IROS 2020 Workshop - Bringing Geometric Methods to Robot Learning, Optimization and Control. Bibtex source
2. Laconte, J., Kasmi, A., Pomerleau, F., Chapuis, R., Malaterre, L., Debain, C., & Aufrère, R. (2020). Lambda-Field: A Continuous Counterpart Of The Bayesian Occupancy Grid For Risk Assessment And Safe Navigation. International Journal of Robotics Research (IJRR). Bibtex source
3. Chahine, G., Vaidis, M., Pomerleau, F., & Pradalier, C. (2020). Mapping in unstructured natural environment: A sensor fusion framework for wearable sensor suites. SN Applied Sciences. Bibtex source
4. Kubelka, V., Dandurand, P., Babin, P., Giguère, P., & Pomerleau, F. (2020). Radio propagation models for differential GNSS based on dense point clouds. Journal of Field Robotics. https://doi.org/10.1002/rob.21988 Bibtex source
5. Tremblay, J.-F., Béland, M., Pomerleau, F., Gagnon, R., & Giguère, P. (2020). Automatic 3D Mapping for Tree Diameter Measurements in Inventory Operations. Journal of Field Robotics. https://doi.org/10.1002/rob.21980 Bibtex source
6. Labussière, M., Laconte, J., & Pomerleau, F. (2020). Geometry Preserving Sampling Method based on Spectral Decomposition for Large-scale Environments. Frontiers in Robotics and AI – Multi-Robot Systems, 7, 134. https://doi.org/10.3389/frobt.2020.572054 Bibtex source
7. Baril, D., Grondin, V., Deschenes, S., Laconte, J., Vaidis, M., Kubelka, V., 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. https://doi.org/10.1109/CRV50864.2020.00034 PDF Bibtex source

2019

1. Roucek, T., Pecka, M., Cizek, P., Petricek, T., Bayer, J., Salansky, V., Hert, D., Petrlik, M., Baca, T., Spurny, V., Pomerleau, F., Kubelka, V., Faigl, J., Zimmermann, K., Saska, M., Svoboda, T., & Krajnik, T. (2019). DARPA Subterranean Challenge: Multi-robotic exploration of underground environments. Proceeding of the Modelling and Simulation for Autonomous System Workshop (MESAS). Bibtex source
2. Laconte, J., Debain, C., Chapuis, R., Pomerleau, F., & Aufrere, R. (2019). Lambda-Field: A Continuous Counterpart of the Bayesian Occupancy Grid for Risk Assessment. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS). Bibtex source
3. Dandurand, P., Babin, P., Kubelka, V., Giguère, P., & Pomerleau, F. (2019). Predicting GNSS satellite visibility from dense point clouds. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics. PDF Bibtex source
4. Dandurand, P. (2019). Application et analyse de GNSS dans l’industrie forestière [Master's thesis, Université Laval]. [https://corpus.ulaval.ca/jspui/handle/20.500.11794/37873?mode=full](https://corpus.ulaval.ca/jspui/handle/20.500.11794/37873?mode=full) Bibtex source
5. Babin, P., Dandurand, P., Kubelka, V., Giguère, P., & Pomerleau, F. (2019). Large-scale 3D Mapping of Subarctic Forests. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics. PDF Slides Bibtex source
6. Tremblay, J.-F., Béland, M., Pomerleau, F., Gagnon, R., & Giguère, P. (2019). Automatic 3D Mapping for Tree Diameter Measurements in Inventory Operations. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics. PDF Slides Bibtex source
7. Tremblay, J.-F. (2019). Forest inventory with a lidar-equipped robot for difficult environments [Master's thesis, Université Laval]. [https://corpus.ulaval.ca/jspui/handle/20.500.11794/37634?mode=full](https://corpus.ulaval.ca/jspui/handle/20.500.11794/37634?mode=full) Bibtex source
8. Pradalier, C., Aravecchia, S., & Pomerleau, F. (2019). Multi-session lake-shore monitoring in visually challenging conditions. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics. Bibtex source
9. Landry, D., Pomerleau, F., & Giguère, P. (2019). CELLO-3D: Estimating the Covariance of ICP in the Real World. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). PDF Bibtex source
10. Babin, P., Giguère, P., & Pomerleau, F. (2019). Analysis of Robust Functions for Registration Algorithms. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). PDF Bibtex source
11. Babin, P. (2019). Analysis of error functions for the iterative closest point algorithm [Master's thesis, Université Laval]. [https://corpus.ulaval.ca/jspui/handle/20.500.11794/37990?mode=full](https://corpus.ulaval.ca/jspui/handle/20.500.11794/37990?mode=full) Bibtex source
12. Laconte, J., Deschênes, S.-P., Labussière, M., & Pomerleau, F. (2019). Lidar Measurement Bias Estimation via Return Waveform Modelling in a Context of 3D Mapping. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). PDF Bibtex source
13. Landry, D. (2019). Data-driven covariance estimation for the iterative closest point algorithm [Master's thesis, Université Laval]. [https://corpus.ulaval.ca/jspui/handle/20.500.11794/34734?mode=full](https://corpus.ulaval.ca/jspui/handle/20.500.11794/34734?mode=full) Bibtex source

2018

1. Labussière, M., Laconte, J., & Pomerleau, F. (2018). Geometry Preserving Sampling Method based on Spectral Decomposition for 3D Registration. ArXiv Preprint ArXiv:1810.01666. Bibtex source
2. Tremblay, J.-F., & Béland, M. (2018). Towards operational marker-free registration of terrestiral lidar data in forests. Colloque du regroupement FRQNT-REPARTI. Bibtex source
3. Babin, P., Pomerleau, F., & Giguère, P. (2018). Improving the robustness of registration algorithm in complex environments. Colloque du regroupement FRQNT-REPARTI. Bibtex source
4. Landry, D., Pomerleau, F., & Giguère, P. (2018). Data-driven covariance estimation of the iterative closest point algorithm. Rendez-vous en intelligence artificielle de Québec. Bibtex source
5. McGarey, P., Yoon, D., Tang, T., Pomerleau, F., & Barfoot, T. D. (2018). Field Report: Developing and Deploying a Tethered Robot to Map Extremely Steep Terrain. Journal of Field Robotics, 35(8), 1327–1241. Bibtex source
6. Tang, T., Yoon, D., Pomerleau, F., & Barfoot, T. D. (2018). Learning a Bias Correction for Lidar-Only Motion Estimation. Proceedings of the 15th Conference on Computer and Robot Vision (CRV). Bibtex source
7. McGarey, P., Yoon, D., Tang, T., Pomerleau, F., & Barfoot, T. D. (2018). Field Deployment of the Tethered Robotic eXplorer to Map Extremely Steep Terrain. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics, 5, 303–317. Bibtex source

2017

1. McGarey, P., MacTavish, K., Pomerleau, F., & Barfoot, T. D. (2017). TSLAM: Tethered simultaneous localization and mapping for mobile robots. The International Journal of Robotics Research, 36(12), 1363–1386. https://doi.org/10.1177/0278364917732639 Bibtex source
2. Pomerleau, F., & Kelly, J. (Eds.). (2017). Journal of Field Robotics (Vol. 34, Number 1, pp. 3–4). Bibtex source
3. Paton, M., Pomerleau, F., MacTavish, K., Ostafew, C. J., & Barfoot, T. D. (2017). Expanding the Limits of Vision-based Localization for Long-term Route-following Autonomy. Journal of Field Robotics, 34(1), 98–122. Bibtex source
4. Hitz, G., Galceran, E., Garneau, M.-È., Pomerleau, F., & Siegwart, R. (2017). Adaptive continuous-space informative path planning for online environmental monitoring. Journal of Field Robotics, 34(8), 1427–1449. Bibtex source

2016

1. Daoust, T., Pomerleau, F., & Barfoot, T. D. (2016). Light at the End of the Tunnel: High-Speed, Lidar-Based Train Localization in Challenging Underground Environments. Proceedings of the 13th Conference on Computer and Robot Vision (CRV). Bibtex source
2. Paton, M., Pomerleau, F., & Barfoot, T. D. (2016). In the dead of winter: Challenging vision-based path following in extreme conditions. Springer Tracts in Advanced Robotics, 113, 563–576. Bibtex source
3. McGarey, P., Pomerleau, F., & Barfoot, T. D. (2016). System design of a tethered robotic explorer (TReX) for 3D mapping of steep terrain and harsh environments. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics, 113, 267–281. Bibtex source
4. McGarey, P., Mactavish, K., Pomerleau, F., & Barfoot, T. D. (2016). The line leading the blind: Towards nonvisual localization and mapping for tethered mobile robots. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2016-June, 4799–4806. Bibtex source
5. Kubelka, V., Reinstein, M., & Svoboda, T. (2016). Improving multimodal data fusion for mobile robots by trajectory smoothing. Robotics and Autonomous Systems, 84, 88–96. Bibtex source
6. Jirku, M., Kubelka, V., & Reinstein, M. (2016). WiFi localization in 3D. 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 4551–4557. Bibtex source
7. Kruijff-Korbayová, I., Freda, L., Gianni, M., Ntouskos, V., Hlaváč, V., Kubelka, V., Zimmermann, E., Surmann, H., Dulic, K., Rottner, W., & others. (2016). Deployment of ground and aerial robots in earthquake-struck amatrice in italy (brief report). 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 278–279. Bibtex source

2015

1. Pomerleau, F., Colas, F., & Siegwart, R. (2015). A Review of Point Cloud Registration Algorithms for Mobile Robotics. Foundations and Trends in Robotics, 4(1), 1–104. Bibtex source
2. Paton, M., Pomerleau, F., & Barfoot, T. D. (2015). Eyes in the Back of Your Head: Robust Visual Teach & Repeat Using Multiple Stereo Cameras. Proceedings of the 12th Conference on Computer and Robot Vision (CRV), 46–53. Bibtex source
3. Krüsi, P., Bücheler, B., Pomerleau, F., Schwesinger, U., Siegwart, R., & Furgale, P. (2015). Lighting-invariant adaptive route following using iterative closest point matching. Journal of Field Robotics, 32(4), 534–564. Bibtex source
4. Hitz, G., Pomerleau, F., Colas, F., & Siegwart, R. (2015). Relaxing the planar assumption: 3D state estimation for an autonomous surface vessel. International Journal of Robotics Research, 34(13), 1604–1621. Bibtex source
5. Kubelka, V., Oswald, L., Pomerleau, F., Colas, F., Svoboda, T., & Reinstein, M. (2015). Robust data fusion of multimodal sensory information for mobile robots. Journal of Field Robotics, 32(4), 447–473. Bibtex source
6. Hitz, G., Pomerleau, F., Colas, F., & Siegwart, R. (2015). State Estimation for Shore Monitoring Using an Autonomous Surface Vessel. Proceedings of the International Symposium on Experimental Robotics (ISER). Springer Tracts in Advanced Robotics, 745–760. Bibtex source
7. Simanek, J., Reinstein, M., & Kubelka, V. (2015). Evaluation of the EKF-based estimation architectures for data fusion in mobile robots. IEEE/ASME Transactions on Mechatronics, 20(2), 985–990. Bibtex source
8. Simanek, J., Kubelka, V., & Reinstein, M. (2015). Improving multi-modal data fusion by anomaly detection. Autonomous Robots, 39(2), 139–154. Bibtex source

2014

1. Kruijff, G. J. M., Kruijff-Korbayová, I., Keshavdas, S., Larochelle, B., Janíček, M., Colas, F., Liu, M., Pomerleau, F., Siegwart, R., Neerincx, M. A., Looije, R., Smets, N. J. J. M., Mioch, T., Van Diggelen, J., Pirri, F., Gianni, M., Ferri, F., Menna, M., Worst, R., … Hlaváč, V. (2014). Designing, developing, and deploying systems to support human-robot teams in disaster response. Advanced Robotics, 28(23), 1547–1570. Bibtex source
2. Kruijff, G. J. M., Janíček, M., Keshavdas, S., Larochelle, B., Zender, H., Smets, N. J. J. M., Mioch, T., Neerincx, M. A., Diggelen, J. V., Colas, F., Liu, M., Pomerleau, F., Siegwart, R., Hlaváč, V., Svoboda, T., Petříček, T., Reinstein, M., Zimmermann, K., Pirri, F., … Sulk, M. (2014). Experience in system design for human-robot teaming in urban search and rescue. Proceedings of 8th International Conference on Field and Service Robotics (FSR), 92, 111–125. Bibtex source
3. Hitz, G., Gotovos, A., Pomerleau, F., Garneau, M.-E., Pradalier, C., Krause, A., & Siegwart, R. Y. (2014). Fully autonomous focused exploration for robotic environmental monitoring. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2658–2664. Bibtex source
4. Pomerleau, F., Krüsi, P., Colas, F., Furgale, P., & Siegwart, R. (2014). Long-term 3D map maintenance in dynamic environments. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 3712–3719. Bibtex source
5. Kubelka, V., & Reinstein, M. (2014). Combining Complementary Motion Estimation Approaches to Increase Reliability in Urban Search & Rescue Missions. International Workshop on Modelling and Simulation for Autonomous Systems, 347–356. Bibtex source

2013

1. Pomerleau, F. (2013). Applied Registration for Robotics: Methodology and Tools for ICP-like Algorithms [PhD thesis]. Eidgenössische Technische Hochschule (ETH) Zurich. Bibtex source
2. Colas, F., Mahesh, S., Pomerleau, F., Liu, M., & Siegwart, R. (2013). 3D path planning and execution for search and rescue ground robots. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 722–727. Bibtex source
3. Pomerleau, F., Colas, F., Siegwart, R., & Magnenat, S. (2013). Comparing ICP variants on real-world data sets: Open-source library and experimental protocol. Autonomous Robots, 34(3), 133–148. Bibtex source
4. Garneau, M.-È., Posch, T., Hitz, G., Pomerleau, F., Pradalier, C., Siegwart, R., & Pernthaler, J. (2013). Short-term displacement of \textitPlanktothrix Rubescens (cyanobacteria) in a pre-alpine lake observed using an autonomous sampling platform. Limnology and Oceanography, 58(5), 1892–1906. Bibtex source
5. Reinstein, M., Kubelka, V., & Zimmermann, K. (2013). Terrain adaptive odometry for mobile skid-steer robots. 2013 IEEE International Conference on Robotics and Automation, 4706–4711. Bibtex source

2012

1. Gemme, S., Gingras, D., Salerno, A., Dupuis, E., Pomerleau, F., & Michaud, F. (2012). Pose Refinement Using ICP Applied to 3-D LIDAR Data for Exploration Rovers. Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space. Bibtex source
2. Pomerleau, F., Breitenmoser, A., Liu, M., Colas, F., & Siegwart, R. (2012). Noise Characterization of Depth Sensors for Surface Inspections. Proceedings of the Applied Robotics for the Power Industry (CARPI). Bibtex source
3. Liu, M., Colas, F., Pomerleau, F., & Siegwart, R. (2012). A Markov semi-supervised clustering approach and its application in topological map extraction. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 4743–4748. Bibtex source
4. Hitz, G., Pomerleau, F., Garneau, M.-E., Pradalier, C., Posch, T., Pernthaler, J., & Siegwart, R. Y. (2012). Autonomous inland water monitoring: Design and application of a surface vessel. IEEE Robotics and Automation Magazine, 19(1), 62–72. Bibtex source
5. Pomerleau, F., Liu, M., Colas, F., & Siegwart, R. (2012). Challenging data sets for point cloud registration algorithms. International Journal of Robotics Research, 31(14), 1705–1711. Bibtex source
6. Liu, M., Pomerleau, F., Colas, F., & Siegwart, R. (2012). Normal estimation for pointcloud using GPU based sparse tensor voting. Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO), 91–96. Bibtex source
7. Liu, M., Pradalier, C., Pomerleau, F., & Siegwart, R. (2012). Scale-only visual homing from an omnidirectional camera. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 3944–3949. Bibtex source
8. Stumm, E., Breitenmoser, A., Pomerleau, F., Pradalier, C., & Siegwart, R. (2012). Tensor-voting-based navigation for robotic inspection of 3D surfaces using lidar point clouds. International Journal of Robotics Research, 31(12), 1465–1488. Bibtex source
9. Liu, M., Pradalier, C., Pomerleau, F., & Siegwart, R. (2012). The role of homing in visual topological navigation. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 567–572. Bibtex source
10. Kubelka, V., & Reinstein, M. (2012). Complementary filtering approach to orientation estimation using inertial sensors only. 2012 IEEE International Conference on Robotics and Automation, 599–605. Bibtex source

2011

1. Gianni, M., Papadakis, P., Pirri, F., Liu, M., Pomerleau, F., Colas, F., Zimmermann, K., Svoboda, T., Petricek, T., Kruijff, G. J. M., Khambhaita, H., & Zender, H. (2011). A unified framework for planning and execution-monitoring of mobile robots: Vol. WS-11-09 (pp. 39–44). AAAI Workshop - Technical Report. Bibtex source
2. Pomerleau, F., Lescot, B., Colas, F., Liu, M., & Siegwart, R. (2011). Dataset acquisitions for USAR environment: Vol. FS-11-05 (pp. 49–54). AAAI Fall Symposium - Technical Report. Bibtex source
3. Tâche, F., Pomerleau, F., Caprari, G., Siegwart, R., Bosse, M., & Moser, R. (2011). Three-dimensional localization for the MagneBike inspection robot. Journal of Field Robotics, 28(2), 180–203. Bibtex source
4. Pomerleau, F., Magnenat, S., Colas, F., Liu, M., & Siegwart, R. (2011). Tracking a depth camera: Parameter exploration for fast ICP. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 3824–3829. Bibtex source

2010

1. Pomerleau, F., & Colas, F. (2010). Evaluation of stereo reconstruction for 3D mapping. 4th International Conference on Cognitive Systems (CogSys). Bibtex source
2. Michaud, F., Boissy, P., Labonté, D., Brire, S., Perreault, K., Corriveau, H., Grant, A., Lauria, M., Cloutier, R., Roux, M.-A., Iannuzzi, D., Royer, M.-P., Ferland, F., Pomerleau, F., & Létourneau, D. (2010). Exploratory design and evaluation of a homecare teleassistive mobile robotic system. Mechatronics, 20(7), 751–766. Bibtex source
3. Tâche, F., Pomerleau, F., Fischer, W., Caprari, G., Mondada, F., Moser, R., & Siegwart, R. (2010). MagneBike: Compact magnetic wheeled robot for power plant inspection. Proceedings of the 1st International Conference on Applied Robotics for the Power Industry (CARPI). Bibtex source
4. Pomerleau, F., Colas, F., Ferland, F., & Michaud, F. (2010). Relative Motion Threshold for Rejection in ICP Registration. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics, 62, 229–238. Bibtex source

2008

1. Pomerleau, F. (2008). Registration algorithm optimized for simultaneous localization and mapping [Master's thesis]. Université de Sherbrooke. Bibtex source
2. Ferland, F., Pomerleau, F., Dinh, C. T. L., & Michaud, F. (2008). Egocentric and exocentric teleoperation interface using real-time, 3D video projection. Proceedings of the 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 37–44. Bibtex source