Publications

2022

  1. Lauri, M., Hsu, D., & Pajarinen, J. (2022). Partially Observable Markov Decision Processes in Robotics: A Survey. To Appear in IEEE Transactions on Robotics, 1–20. https://doi.org/10.1109/TRO.2022.3200138
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  2. Nicke, T., Graf, L., Lauri, M., Mischkewitz, S., Frintrop, S., & Heinrich, M. P. (2022). Cross domain knowledge compression in realtime optical flow prediction on ultrasound sequences. 10th International Workshop on Biomedical Image Registration. https://openreview.net/forum?id=B0zu87RnqRF
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  3. Sarhan, N., Lauri, M., & Frintrop, S. (2022). Multi-phase Fine-Tuning: A New Fine-Tuning Approach for Sign Language Recognition. KI - Künstliche Intelligenz, 36, 91–98. https://doi.org/10.1007/s13218-021-00746-2
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2021

  1. Banik, S., Lauri, M., Knoll, A. C., & Frintrop, S. (2021). Object Localization with Attribute Preference Based on Top-Down Attention. Proc. 13th International Conference on Computer Vision Systems (ICVS 2021), 28–40. https://doi.org/10.1007/978-3-030-87156-7_3
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  2. Gao, G., Lauri, M., Hu, X., Zhang, J., & Frintrop, S. (2021). CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds. Proc. IEEE Intl. Conf. on Robotics and Automation (ICRA 2021), 11081–11087. https://doi.org/10.1109/ICRA48506.2021.9561475
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2020

  1. Nguyen, Q., Richter, J., Lauri, M., Gerkmann, T., & Frintrop, S. (2020). Improving Mix-And-Separate Training in Audio-Visual Sound Source Separation with an Object Prior. Proc. 25th International Confererence on Pattern Recognition (ICPR 2020), 5844–5851. https://doi.org/10.1109/ICPR48806.2021.9412174
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  2. Lauri, M., & Oliehoek, F. A. (2020). Multi-agent active perception with prediction rewards. Advances in Neural Information Processing Systems 33 (NeurIPS 2020). https://proceedings.neurips.cc/paper/2020/hash/9db6faeef387dc789777227a8bed4d52-Abstract.html
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  3. Lauri, M., Pajarinen, J., Peters, J., & Frintrop, S. (2020). Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization. IEEE Robotics and Automation Letters, 5(4), 5323–5330. https://doi.org/10.1109/LRA.2020.3007445
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  4. Lauri, M., Pajarinen, J., & Peters, J. (2020). Multi-agent active information gathering in discrete and continuous-state decentralized POMDPs by policy graph improvement. Autonomous Agents and Multi-Agent Systems, 34(42). https://doi.org/10.1007/S10458-020-09467-6
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  5. Gao, G., Lauri, M., Wang, Y., Hu, X., Zhang, J., & Frintrop, S. (2020). 6D Object Pose Regression via Supervised Learning on Point Clouds. Proc. IEEE Intl. Conf. on Robotics and Automation (ICRA), 3643–3649. https://doi.org/10.1109/ICRA40945.2020.9197461
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2019

  1. Lauri, M., Pajarinen, J., & Peters, J. (2019). Information Gathering in Decentralized POMDPs by Policy Graph Improvement. Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1143–1151. https://dl.acm.org/doi/abs/10.5555/3306127.3331815
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  2. Karl, F., Lauri, M., & Biemann, C. (2019, October). Creating Information-maximizing Natural Language Messages Through Image Captioning-Retrieval. Proceedings of the 15th Conference on Natural Language Processing (KONVENS 2019). https://konvens.org/proceedings/2019/papers/KONVENS2019_paper_22.pdf
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  3. Schmid, J. F., Lauri, M., & Frintrop, S. (2019, November). Explore, Approach, and Terminate: Evaluating Subtasks in Active Visual Object Search Based on Deep Reinforcement Learning. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS). https://doi.org/10.1109/IROS40897.2019.8967805
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  4. Nguyen, Q., Lauri, M., & Frintrop, S. (2019, August). Distance Dependent Maximum Margin Dirichlet Process Mixture. 16th Pacific Rim International Conference on Artificial Intelligence (PRICAI). https://doi.org/10.1007/978-3-030-29911-8_15
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  5. Lauri, M., Pajarinen, J., Peters, J., & Frintrop, S. (2019, June). Approximation of joint information gain for multi-sensor volumetric scene reconstruction. 2nd Workshop on Informative Path Planning and Adaptive Sampling.
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  6. Lauri, M., Pajarinen, J., & Peters, J. (2019, June). Sampling-based policy graph improvement in decentralized POMDPs for information gathering. 2nd Workshop on Informative Path Planning and Adaptive Sampling.
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2018

  1. Banik, S., Lauri, M., & Frintrop, S. (2018). Multi-label Object Attribute Classification using a Convolutional Neural Network.
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  2. Gao, G., Lauri, M., Zhang, J., & Frintrop, S. (2018). Occlusion Resistant Object Rotation Regression from Point Cloud Segments. ECCV 2018 Workshops: 4th International Workshop on Recovering 6D Object Pose, 716–729. https://doi.org/10.1007/978-3-030-11009-3_44
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2017

  1. Lauri, M., Ropponen, A., & Ritala, R. (2017). Meeting a deadline: shortest paths on stochastic directed acyclic graphs with information gathering. Annals of Mathematics and Artificial Intelligence, 79(4), 337–370. https://doi.org/10.1007/s10472-016-9527-5
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  2. Gao, G., Lauri, M., Zhang, J., & Frintrop, S. (2017). Saliency-guided Adaptive Seeding for Supervoxel Segmentation. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 4938–4943. https://doi.org/10.1109/IROS.2017.8206374
    [DOI] [arXiv] [Code] [Show/hide BibTeX] [Copy BibTeX to clipboard]
  3. Lauri, M., & Frintrop, S. (2017). Object proposal generation applying the distance dependent Chinese restaurant process. Scandinavian Conference on Image Analysis (SCIA), 260–272. https://doi.org/10.1007/978-3-319-59126-1_22
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  4. Lauri, M., Heinänen, E., & Frintrop, S. (2017). Multi-Robot Active Information Gathering with Periodic Communication. IEEE Intl. Conf. on Robotics and Automation (ICRA), 851–856. https://doi.org/10.1109/ICRA.2017.7989104
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2016

  1. Lauri, M., & Ritala, R. (2016). Planning for robotic exploration based on forward simulation. Robotics and Autonomous Systems, 83, 15–31. https://doi.org/10.1016/j.robot.2016.06.008
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  2. Hytti, H., Nissinen, A., Lauri, M., Koivisto, H., Ihalainen, H., & Ritala, R. (2016). Automatic Selection Of Relevant Data For Paper Machine Diagnostics. Journal of Science and Technology for Forest Products and Processes, 5(2), 32–42.
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  3. Lauri, M., Atanasov, N., Pappas, G., & Ritala, R. (2016). Myopic Policy Bounds for Information Acquisition POMDPs.
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  4. Ropponen, A., Lauri, M., & Ritala, R. (2016). Risk-averse path planning with observation options. In A. Finzi & E. Karpas (Eds.), Proc. of the 4th Workshop on Planning and Robotics (PlanRob) (pp. 25–35).
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2015

  1. Kolu, A., Lauri, M., Hyvönen, M., Ghabcheloo, R., & Huhtala, K. (2015). A mapping method tolerant to calibration and localization errors based on tilting 2D laser scanner. Proc. European Control Conference (ECC), 2348–2353. https://doi.org/10.1109/ECC.2015.7330889
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  2. Lauri, M., & Ritala, R. (2015). Optimal Sensing via Multi-armed Bandit Relaxations in Mixed Observability Domains. Proc. IEEE Intl. Conf. on Robotics and Automation (ICRA), 4807–4812. https://doi.org/10.1109/ICRA.2015.7139867
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  3. Lauri, M., Atanasov, N., Pappas, G., & Ritala, R. (2015, May). Active Object Recognition via Monte Carlo Tree Search. ICRA Workshop on Beyond Geometric Constraints.
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  4. Melin, J., Lauri, M., Kolu, A., Koljonen, J., & Ritala, R. (2015). Cooperative Sensing and Path Planning in a Multi-vehicle Environment. IFAC Workshop on Advanced Control and Navigation for Autonomous Aerospace Vehicles (ACNAAV), 198–203. https://doi.org/10.1016/j.ifacol.2015.08.083
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2014

  1. Melin, J., Lauri, M., & Ritala, R. (2014, August). Stereo vision with consumer grade high resolution cameras for a micro air vehicle. International Micro Air Vehicle Conference and Competition. https://doi.org/10.4233/uuid:77aa1242-b1b3-453c-8aa7-5acb09ac219b
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  2. Lauri, M., & Ritala, R. (2014, May). Stochastic control for maximizing mutual information in active sensing. ICRA Workshop on Robots in Homes and Industry: Where to Look First? https://tutcris.tut.fi/portal/en/publications/stochastic-control-for-maximizing-mutual-information-in-active-sensing(69c5773d-4a2a-4ba7-ab11-e93f529e612d).html
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2013

  1. Lauri, M., & Ritala, R. (2013). Planning for multiple measurement channels in a continuous-state POMDP. Annals of Mathematics and Artificial Intelligence, 67, 283–317. https://doi.org/10.1007/s10472-013-9361-y
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  2. Lauri, M., & Ritala, R. (2013). Path Planning in Dynamic Environments with the Partially Observable Canadian Traveller’s Problem. In A. Finzi, F. Ingrand, & A. Orlandini (Eds.), Proc. of the 1st Workshop on Planning and Robotics (PlanRob) (pp. 89–95).
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2012

  1. Lauri, M., & Ritala, R. (2012, September). Receding horizon control for selection of focus of attention. Proc. of The 20th IMEKO World Congress.
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2011

  1. Björninen, T., Lauri, M., Ukkonen, L., Ritala, R., Elsherbeni, A. Z., & Sydanheimo, L. (2011). Wireless Measurement of RFID IC Impedance. IEEE Transactions on Instrumentation and Measurement, 60(9), 3194–3206. https://doi.org/10.1109/TIM.2011.2123190
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  2. Kumpulainen, P., Mettänen, M., Lauri, M., & Ihalainen, H. (2011). Relating halftone dot quality to paper surface topography. Neural Computing and Applications, 20(6), 803–813. https://doi.org/10.1007/s00521-010-0497-y
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  3. Björninen, T., Lauri, M., Koski, K., Ukkonen, L., Elsherbeni, A., Ritala, R., & Sydänheimo, L. (2011). Wireless Measurement of Wake-Up Power and Impedance of UHF RFID IC. Proc. of the 33rd Antenna Measurement Techniques Association (AMTA) Symposium, 63–68.
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2010

  1. Björninen, T., Lauri, M., Ukkonen, L., Sydänheimo, L., Elsherbeni, A., & Ritala, R. (2010). Wireless Measurement of UHF RFID Chip Impedance. Proc. of the 32nd Antenna Measurement Techniques Association (AMTA) Symposium, 35–40.
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  2. Lauri, M., & Ihalainen, H. (2010, April). Measuring Periodic Patterns in Noisy Spatial Data. ENBIS-IMEKO TC21 Workshop on Measurement Systems and Process Improvement.
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2009

  1. Kumpulainen, P., Mettänen, M., Lauri, M., & Ihalainen, H. (2009). Relating Halftone Dot Quality to Paper Surface Topography. Proc. 11th Intl. Conf. on Engineering Applications of Neural Networks (EANN), 178–189. https://doi.org/10.1007/978-3-642-03969-0_17
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  2. Mettänen, M., Hirn, U., Lauri, M., & Ritala, R. (2009, September). Probabilistic Analysis of Small-scale Print Defects with Aligned 2D Measurements. Transactions of the 14th Fundamental Research Symposium.
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  3. Mettänen, M., Lauri, M., Ihalainen, H., Kumpulainen, P., & Ritala, R. (2009, June). Aligned Analysis of Surface Topography and Printed Dot Pattern Maps. Proc. of the Papermaking Research Symposium. https://tutcris.tut.fi/portal/en/publications/aligned-analysis-of-surface-topography-and-printed-dot-pattern-maps(f5324948-1bbe-4879-b649-79acd52608d7).html
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