My picture

Michael Kaess

Associate Research Professor
Field Robotics Center (FRC)
Robotics Institute (RI)
School of Computer Science (SCS)
Carnegie Mellon University (CMU)

Director, Robot Perception Lab (RPL)

5000 Forbes Ave, Room NSH 1617
Pittsburgh, PA 15213-3890
Phone: (678)365-1243, Email: kaess@cmu.edu

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.

Curriculum Vitae (CV)

News

Selected Publications   [All Publications...]

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.

Dense Surface Reconstruction from Monocular Vision and LiDAR by Z. Li, P.C. Gogia, and M. Kaess. In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Montreal, Canada), May 2019, pp. 6905-6911. 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.

Last updated: May 26, 2020