I am interested in mobile robot autonomy. One of the first
problems encountered when robots operate outside controlled factory
and research environments is the need to perceive their surroundings. My
research focuses on efficient inference at the connection of linear
algebra and probabilistic graphical models for 3D mapping and
localization.
I have previously been a Research Scientist and a Postdoctoral
Associate at the Massachusetts Institute of Technology (MIT), in
John Leonard's Marine
Robotics Lab. In 2008 I have received my PhD in Computer Science from
the Georgia Institute of Technology, advised
by Frank Dellaert.
Jul 2020: Frank Dellaert and I received the Inaugural RSS 2020 Test of Time Award "For pioneering an information smoothing approach to the SLAM problem via square root factorization, its interpretation as a graphical model, and the widely-used GTSAM free software repository."
Oct 2014: I am Associate Editor for ICRA 2015, which will be held in Seattle.
Sep 2014: We have tested our in-water ship inspection robot on the NS Savannah, the first nuclear powered passenger and cargo ship, and a national historic landmark.
Aug 2014: I received a Google Faculty Research Award.
Neural feels with neural fields: Visuo-tactile perception for in-hand manipulation by S. Suresh, H. Qi, T. Wu, T. Fan, L. Pineda, M. Lambeta, J. Malik, M. Kalakrishnan, R. Calandra, M. Kaess, J. Ortiz, and M. Mukadam. AAAS Science Robotics, vol. 9, no. 96, Nov. 2024. Details. Download: PDF.
HoloOcean: A full-featured marine robotics simulator for perception and autonomy by E. Potokar, K. Lay, K. Norman, D. Benham, S. Ashford, R. Peirce, T. Neilsen, M. Kaess, and J. Mangelson. IEEE J. of Oceanic Engineering, JOE, vol. 49, no. 4, pp. 1322-1336, Oct. 2024. Details. Download: PDF.
Asynchronous distributed smoothing and mapping via on-manifold consensus ADMM by D. McGann, K. Lassak, and M. Kaess. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, Yokohama, Japan, May 2024, pp. 4577-4583. Best multi-robot systems paper finalist (one of five). Details. Download: PDF.
Robust incremental smoothing and mapping (riSAM) by D. McGann, J. Rogers III, and M. Kaess. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, London, UK, May 2023, pp. 4157-4163. Details. Downlaod: PDF.
Neural implicit surface reconstruction using imaging sonar by M. Qadri, M. Kaess, and I. Gkioulekas. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, London, UK, May 2023, pp.
1040-1047. Details. Download: PDF.
ASH: A modern framework for parallel spatial hashing in 3D perception by W. Dong, Y. Lao, M. Kaess, and V. Koltun. IEEE Trans. on Pattern Analysis and Machine Intelligence, PAMI, vol. 45, no. 5, pp. 5417-5435, May 2023. Details. Download: PDF.
MidasTouch: Monte-Carlo inference over distributions across sliding touch by S. Suresh, Z. Si, S. Anderson, M. Kaess, and M. Mukadam. In Proc. Conf. on Robot Learning, CoRL, Auckland, New Zealand, Dec. 2022. Details. Download: PDF.
InCOpt: Incremental constrained optimization using the Bayes tree by M. Qadri, P. Sodhi, J. Mangelson, F. Dellaert, and M. Kaess. In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, Kyoto, Japan, Oct. 2022, pp. 6381-6388. Details. Download: PDF.
LEO: Learning Energy-based Models in Factor Graph Optimization by P. Sodhi, M. Mukadam, S. Anderson, and M. Kaess. In Proc. Conf. on Robot Learning, CoRL, (London, UK), Nov. 2021. Details. Download: PDF.
ICS: Incremental Constrained Smoothing for State Estimation by P. Sodhi, S. Choudhury, J.G. Mangelson, and M. Kaess. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Paris, France), May 2020. Details Download: PDF.
Active SLAM using 3D Submap Saliency for Underwater Volumetric Exploration by S. Suresh, P. Sodhi, J.G. Mangelson, D. Wettergreen, and M. Kaess. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Paris, France), May 2020. Details. Download: PDF.
A Volumetric Albedo Framework for 3D Imaging Sonar Reconstruction by E. Westman, I. Gkioulekas, and M. Kaess. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Paris, France), May 2020. Details. Download: PDF.
GPU Accelerated Robust Scene Reconstruction by W. Dong, J. Park, Y. Yang, and M. Kaess. In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Macao), Nov. 2019, pp. 7863-7870. Details. Download: PDF.
Online and Consistent Occupancy Grid Mapping for Planning in Unknown Environments by P. Sodhi, B. Ho, and M. Kaess. In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Macao), Nov. 2019, pp. 7879-7886. Details. Download: PDF.
MH-iSAM2: Multi-hypothesis iSAM using Bayes Tree and Hypo-tree by M. Hsiao and M. Kaess. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Montreal, Canada), May 2019, pp. 1274-1280. Details. Download: PDF.
Information Sparsification in Visual-Inertial Odometry by J. Hsiung, M. Hsiao, E. Westman, R. Valencia, and M. Kaess. In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Madrid, Spain), Oct. 2018. Best conference paper finalist (one of six). Details. Download: PDF.
Factor Graphs for Robot Perception by F. Dellaert and M. Kaess. Foundations and Trends in Robotics, vol. 6, no. 1-2, Aug. 2017, pp. 1-139. Details. Download: PDF.
Articulated Robot Motion for Simultaneous Localization and Mapping (ARM-SLAM) by M. Klingensmith, S. Srinivasa, and M. Kaess. IEEE Robotics and Automation Letters (RA-L), 2016. Part of ICRA/RA-L: presented at ICRA 2016 and published in RA-L. Best vision paper finalist (one of five). Details. Download: PDF.
Real-time Large Scale Dense RGB-D SLAM with Volumetric Fusion by T. Whelan, M. Kaess, H. Johannsson, M.F. Fallon, J.J. Leonard, and J.B. McDonald. Intl. J. of Robotics Research, IJRR, vol. 34, no. 4-5, Apr. 2015, pp. 598-626. Details. Download: PDF.
RISE: An Incremental Trust-Region Method for Robust Online Sparse Least-Squares Estimation by D.M. Rosen, M. Kaess, and J.J. Leonard. IEEE Trans. on Robotics, TRO, vol. 30, no. 5, Oct. 2014, pp. 1091-1108. Details. Download: PDF.
Temporally Scalable Visual SLAM using a Reduced Pose Graph by H. Johannsson, M. Kaess, M.F. Fallon, and J.J. Leonard. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Karlsruhe, Germany), May 2013. Best student paper finalist (one of five). Details. Download: PDF.
Advanced Perception, Navigation and Planning for Autonomous In-Water Ship Hull Inspection by F.S. Hover, R.M. Eustice, A. Kim, B.J. Englot, H. Johannsson, M. Kaess, and J.J. Leonard. Intl. J. of Robotics Research, IJRR, vol. 31, no. 12, Oct. 2012, pp. 1445-1464. Details. Download: PDF.
iSAM2: Incremental Smoothing and Mapping Using the Bayes Tree by M. Kaess, H. Johannsson, R. Roberts, V. Ila, J.J. Leonard, and F. Dellaert. Intl. J. of Robotics Research, IJRR, vol. 31, Feb. 2012, pp. 217-236. Details. Download: PDF.
Multiple Relative Pose Graphs for Robust Cooperative Mapping by B. Kim, M. Kaess, L. Fletcher, J.J. Leonard, A. Bachrach, N. Roy, and S. Teller. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Anchorage, Alaska), May 2010, pp. 3185-3192. Details. Download: PDF.
Covariance Recovery from a Square Root Information Matrix for Data Association by M. Kaess and F. Dellaert. Journal of Robotics and Autonomous Systems, vol. 57, Dec. 2009, pp. 1198-1210. Details. Download: PDF.
iSAM: Incremental Smoothing and Mapping by M. Kaess, A. Ranganathan, and F. Dellaert. IEEE Trans. on Robotics, vol. 24, no. 6, Dec. 2008, pp. 1365-1378. Details. Download: PDF.
Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing by F. Dellaert and M. Kaess. Intl. J. of Robotics Research, vol. 25, no. 12, Dec. 2006, pp. 1181-1204. Details. Download: PDF.