Home/Michael Kaess

Michael Kaess

Assistant Research Professor
Email: kaess@andrew.cmu.edu
Office: NSH 1617
Phone: (412) 268-6905
Personal Homepage

Perception is a fundamental challenge for mobile robots navigating through and interacting with their environment. My research focuses on 3D mapping and localization using information from any available sensor, including vision, laser, inertial, GPS and sonar (underwater). To enable online operation, my research also explores novel algorithms for efficient and robust inference at the intersection of linear algebra and probabilistic graphical models.

Publications

Displaying 75 Publications
GravityFusion: Real-time Dense mapping without Pose Graph using Deformation and Orientation
Puneet Puri, Daoyuan Jia and Michael Kaess

Conference Paper, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, September, 2017
Keyframe-based Dense Planar SLAM
Ming Hsiao, Eric Westman, Guofeng Zhang and Michael Kaess

Conference Paper, IEEE Intl. Conf. on Robotics and Automation, ICRA, May, 2017
Robust Stereo Matching with Surface Normal Prediction
Shuangli Zhang, Weijian Xie, Guofeng Zhang, Hujun Bao and Michael Kaess

Conference Paper, IEEE Intl. Conf. on Robotics and Automation, ICRA, May, 2017
The Manifold Particle Filter for State Estimation on High-dimensional Implicit Manifolds
Michael C. Koval, Matthew Klingensmith, Siddhartha S. Srinivasa, Nancy Pollard and Michael Kaess

Conference Paper, IEEE Intl. Conf. on Robotics and Automation, ICRA, May, 2017
Direct Visual Odometry in Low Light using Binary Descriptors
Hatem Alismail, Michael Kaess, Brett Browning and Simon Lucey

Journal Article, IEEE Robotics and Automation Letters, RA-L, Vol. 2, pp. 444-451, April, 2017
A Real-time Method for Depth Enhanced Monocular Odometry
Ji Zhang, Michael Kaess and Sanjiv Singh

Journal Article, Autonomous Robots, AURO, Vol. 41, No. 1, pp. 31-43, January, 2017
A Nonparametric Belief Solution to the Bayes Tree
Dehann Fourie, John J. Leonard and Michael Kaess

Conference Paper, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, October, 2016
Incremental Data Association for Acoustic Structure from Motion
Tiffany Huang and Michael Kaess

Conference Paper, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, October, 2016
Long-range GPS-denied Aerial Inertial Navigation with LIDAR Localization
Garrett Hemann, Sanjiv Singh and Michael Kaess

Conference Paper, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, October, 2016
Pop-up SLAM: Semantic Monocular Plane SLAM for Low-texture Environments
Shichao Yang, Yu Song, Michael Kaess and Sebastian Scherer

Conference Paper, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October, 2016
Underwater Inspection using Sonar-based Volumetric Submaps
Pedro V. Teixeira, Michael Kaess, Franz S. Hover and John J. Leonard

Conference Paper, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, October, 2016
On Degeneracy of Optimization-based State Estimation Problems
Ji Zhang, Michael Kaess and Sanjiv Singh

Conference Paper, Carnegie Mellon University, 2016 IEEE International Conference on Robotics and Automation, May, 2016
Articulated Robot Motion for Simultaneous Localization and Mapping (ARM-SLAM)
Matthew Klingensmith, Siddhartha Srinivasa and Michael Kaess

Journal Article, IEEE Robotics and Automation - Letters, January, 2016
Bridging Text Spotting and SLAM with Junction Features
Hsueh-Cheng Wang, Chelsea Finn, Liam Paull, Michael Kaess, Ruth Rosenholtz, Seth Teller and John Leonard

Conference Paper, Carnegie Mellon University, In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, pp. 3701-3708, September, 2015
Towards Acoustic Structure from Motion for Imaging Sonar
Tiffany Huang and Michael Kaess

Conference Paper, Carnegie Mellon University, In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, pp. 758-765, September, 2015
Consistent Unscented Incremental Smoothing for Multi-robot Cooperative Target Tracking
Guoquan Huang, Michael Kaess and John J. Leonard

Journal Article, Carnegie Mellon University, Journal of Robotics and Autonomous Systems, Vol. 69, pp. 52-67, July, 2015
Building 3D Mosaics from an Autonomous Underwater Vehicle, Doppler Velocity Log, and 2D Imaging Sonar
Paul Ozog, Giancarlo Troni, Michael Kaess, Ryan M. Eustice and Matthew Johnson-Roberson

Journal Article, Carnegie Mellon University, In IEEE Intl. Conf. on Robotics and Automation, May, 2015
Simultaneous Localization and Mapping with Infinite Planes
Michael Kaess

Journal Article, Carnegie Mellon University, In IEEE Intl. Conf. on Robotics and Automation, May, 2015
Real-time large scale dense RGB-D SLAM with volumetric fusion
Thomas Whelan, Michael Kaess, Hordur Johannsson, Maurice Fallon, John J. Leonard and John McDonald

Conference Paper, Carnegie Mellon University, The International Journal of Robotics Research, Vol. 34, pp. 598-626, April, 2015
RISE: An Incremental Trust-Region Method for Robust Online Sparse Least-Squares Estimation
David M. Rosen, Michael Kaess and John J. Leonard

Journal Article, Carnegie Mellon University, IEEE Trans. on Robotics, TRO, Vol. 30, No. 5, pp. 1091-1108, October, 2014
Generic Node Removal for Factor-Graph SLAM
Nicholas Carlevaris-Bianco, Michael Kaess and Ryan M. Eustice

Journal Article, Carnegie Mellon University, IEEE Robotics and Automation Society, Vol. 30, No. 6, September, 2014
Real-time Depth Enhanced Monocular Odometry
Ji Zhang, Michael Kaess and Sanjiv Singh

Conference Paper, Carnegie Mellon University, Intelligent Robots and Systems (IROS), Chicago, IL, USA, September, 2014
3D mapping, localisation and object retrieval using low cost robotic platforms: A robotic search engine for the real-world
Thomas Whelan, Michael Kaess, Ross Finman, Maurice Fallon, Hordur Johannsson, John J. Leonard and John McDonald

Journal Article, Carnegie Mellon University, In RSS Workshop on RGB-D: Advanced Reasoning with Depth Cameras, July, 2014
Efficient Incremental Map Segmentation in Dense RGB-D Maps
Ross Finman, Thomas Whelan, Michael Kaess and John J. Leonard

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, (Hong Kong), June, 2014
Towards Consistent Visual-Inertial Navigation
Guoquan Huang, Michael Kaess and John J. Leonard

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, June, 2014
Mapping 3D Underwater Environments with Smoothed Submaps
Mark VanMiddlesworth, Michael Kaess, Franz Hover and John J. Leonard

Conference Paper, Carnegie Mellon University, Conference on Field and Service Robotics (FSR), December, 2013
The MIT Stata Center Dataset
M. Fallon, H. Johannsson, Michael Kaess and J.J. Leonard

Journal Article, Carnegie Mellon University, Intl. J. of Robotics Research, IJRR, Vol. 32, No. 14, pp. 1695-1699, December, 2013
Deformation-based Loop Closure for Large Scale Dense RGB-D SLAM
Thomas Whelan, Michael Kaess, John J. Leonard and John McDonald

Conference Paper, Carnegie Mellon University, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), November, 2013
Real-time 6-DOF Multi-session Visual SLAM over Large Scale Environments
J.B. McDonald, Michael Kaess, C. Cadena, J. Neira and J.J. Leonard

Journal Article, Carnegie Mellon University, Journal of Robotics and Autonomous Systems, RAS, Vol. 61, No. 10, pp. 1144-1158, October, 2013
Consistent Sparsification for Graph Optimization
Guoquan Huang, Michael Kaess and John J. Leonard

Conference Paper, Carnegie Mellon University, European Conference on Mobile Robots (ECMR), September, 2013
Toward Lifelong Object Segmentation from Change Detection in Dense RGB-D Maps
Ross Finman, Thomas Whelan, Michael Kaess and John J. Leonard

Conference Paper, Carnegie Mellon University, European Conference on Mobile Robots (ECMR), September, 2013
Unscented iSAM: A Consistent Incremental Solution to Cooperative Localization and Target Tracking
Guoquan Huang, Robert Truax, Michael Kaess and John J. Leonard

Conference Paper, Carnegie Mellon University, European Conference on Mobile Robots (ECMR), September, 2013
Information Fusion in Navigation Systems via Factor Graph Based Incremental Smoothing
V. Indelman, S. Williams, Michael Kaess and F. Dellaert

Journal Article, Carnegie Mellon University, Journal of Robotics and Autonomous Systems, RAS, Vol. 61, No. 8, pp. 721-738, August, 2013
Analytically-Selected Multi-Hypothesis Incremental Map Estimation
Guoquan Huang, Michael Kaess, John Leonard and Stergios I. Roumeliotis

Conference Paper, Carnegie Mellon University, Intl. Conf. on Acoustics, Speech, and Signal Proc. (ICASSP), May, 2013
Robust Incremental Online Inference Over Sparse Factor Graphs: Beyond the Gaussian Case
David M. Rosen, Michael Kaess and John J. Leonard

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, May, 2013
Robust Real-Time Visual Odometry for Dense RGB-D Mapping
Thomas Whelan, Hordur Johannsson, Michael Kaess, John J. Leonard and John McDonald

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, May, 2013
Temporally Scalable Visual SLAM using a Reduced Pose Graph
Hordur Johannsson, Michael Kaess, Maurice Fallon and John J. Leonard

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, Best student paper finalist (one of five)., May, 2013
Autonomous Flight in GPS-Denied Environments Using Monocular Vision and Inertial Sensors
A. D. Wu, E. N. Johnson, Michael Kaess, F. Dellaert and G. Chowdhary

Journal Article, Carnegie Mellon University, AIAA J. of Aerospace Information Systems (JAIS), Vol. 10, No. 4, pp. 172-186, April, 2013
Advanced Perception, Navigation and Planning for Autonomous In-Water Ship Hull Inspection
Franz S. Hover, Ryan M. Eustice, Ayoung Kim, Brendan Englot, Hordur Johannsson, Michael Kaess and John J. Leonard

Journal Article, Carnegie Mellon University, Intl. J. of Robotics Research, IJRR, Vol. 31, No. 12, pp. 1445-1464, October, 2012
Dynamic Pose Graph SLAM: Long-term Mapping in Low Dynamic Environments
Aisha Walcott-Bryant, Michael Kaess, Hordur Johannsson and John J. Leonard

Conference Paper, Carnegie Mellon University, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, pp. 1871-1878, October, 2012
Robust Tracking for Real-Time Dense RGB-D Mapping with Kintinuous
Thomas Whelan, Hordur Johannsson, Michael Kaess, John J. Leonard and John McDonald

Journal Article, Carnegie Mellon University, Computer Science and Artificial Intelligence Laboratory Technical Report MIT-CSAIL-TR-2012-031, September, 2012
Concurrent Filtering and Smoothing
Michael Kaess, Stephen Williams, Vadim Indelman, Richard Roberts, John J. Leonard and Frank Dellaert

Conference Paper, Carnegie Mellon University, Intl. Conf. on Information Fusion, FUSION, pp. 1300-1307, July, 2012
Concurrent Filtering and Smoothing: A Parallel Architecture for Real-Time Navigation and Full Smoothing
Stephen Williams, Vadim Indelman, Michael Kaess, Richard Roberts, John J. Leonard and Frank Dellaert

Journal Article, Carnegie Mellon University, International Conference on Information Fusion, pp. 1300-1307, July, 2012
Factor Graph Based Incremental Smoothing in Inertial Navigation Systems
Vadim Indelman, Stephen Williams, Michael Kaess and Frank Dellaert

Conference Paper, Carnegie Mellon University, Intl. Conf. on Information Fusion, pp. 2154-2161, July, 2012
Kintinuous: Spatially Extended KinectFusion
Thomas Whelan, John McDonald, Michael Kaess, Maurice Fallon, Hordur Johannsson and John J. Leonard

Conference Paper, Carnegie Mellon University, RSS Workshop on RGB-D: Advanced Reasoning with Depth Cameras, July, 2012
Mapping the MIT Stata Center: Large-scale Integrated Visual and RGB-D SLAM
Maurice F. Fallon, Hordur Johannsson, Michael Kaess, David M. Rosen, Elias Muggler and John J. Leonard

Journal Article, Carnegie Mellon University, RSS Workshop on RGB-D: Advanced Reasoning with Depth Cameras, July, 2012
Temporally Scalable Visual SLAM using a Reduced Pose Graph
Hordur Johannsson, Michael Kaess, Maurice Fallon and John J. Leonard

Conference Paper, Carnegie Mellon University, RSS Workshop on Long-term Operation of Autonomous Robotic Systems in Changing Environments, July, 2012
An Incremental Trust-Region Method for Robust Online Sparse Least-Squares Estimation
David M. Rosen, Michael Kaess and John J. Leonard

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, pp. 1262-1269, May, 2012
iSAM2: Incremental Smoothing and Mapping Using the Bayes Tree
Michael Kaess, Hordur Johannsson, Richard Roberts, Viorela Ila, John Leonard and Frank Dellaert

Journal Article, Carnegie Mellon University, Intl. J. of Robotics Research, IJRR, Vol. 31, No. 2, pp. 217-236, February, 2012
6-DOF Multi-session Visual SLAM using Anchor Nodes
John McDonald, Michael Kaess, Cesar Cadena, Jos Neira and John J. Leonard

Conference Paper, Carnegie Mellon University, European Conference on Mobile Robots, ECMR, pp. 69-76, September, 2011
Efficient AUV Navigation Fusing Acoustic Ranging and Side-scan Sonar
Maurice F. Fallon, Michael Kaess, Hordur Johannsson and John J. Leonard

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA. Best automation paper finalist (one of five)., pp. 2398-2405, May, 2011
iSAM2: Incremental Smoothing and Mapping with Fluid Relinearization and Incremental Variable Reordering
Michael Kaess, Hordur Johannsson, Richard Roberts, Viorela Ila, John Leonard and Frank Dellaert

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, pp. 3281-3288, May, 2011
The Bayes Tree: An Algorithmic Foundation for Probabilistic Robot Mapping
Michael Kaess, Viorela Ila, Richard Roberts and Frank Dellaert

Conference Paper, Carnegie Mellon University, Intl. Workshop on the Algorithmic Foundations of Robotics, WAFR, pp. 157-173, December, 2010
Imaging Sonar-Aided Navigation for Autonomous Underwater Harbor Surveillance
Hordur Johannsson, Michael Kaess, Brendan Englot, Franz Hover and John Leonard

Conference Paper, Carnegie Mellon University, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, October, 2010
Multiple Relative Pose Graphs for Robust Cooperative Mapping
Been Kim, Michael Kaess, Luke Fletcher, John Leonard, Abraham Bachrach, Nicholas Roy and Seth Teller

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, pp. 3185-3192, May, 2010
Towards Autonomous Ship Hull Inspection using the Bluefin HAUV
Michael Kaess, Hordur Johannsson, Brendan Englot, Franz Hover and John Leonard

Miscellaneous, Carnegie Mellon University, Ninth International Symposium on Technology and the Mine Problem, May, 2010
Probabilistic Structure Matching for Visual SLAM with a Multi-Camera Rig
Michael Kaess and Frank Dellaert

Journal Article, Carnegie Mellon University, Computer Vision and Image Understanding, CVIU, Vol. 114, No. 2, pp. 286-296, February, 2010
The Bayes Tree: Enabling Incremental Reordering and Fluid Relinearization for Online Mapping
Michael Kaess, Viorela Ila, Richard Roberts and Frank Dellaert

Journal Article, Carnegie Mellon University, Computer Science and Artificial Intelligence Laboratory - Technical Report MIT-CSAIL-TR-2010-021, January, 2010
Covariance Recovery from a Square Root Information Matrix for Data Association
Michael Kaess and Frank Dellaert

Journal Article, Carnegie Mellon University, Journal of Robotics and Autonomous Systems, RAS, Vol. 57, No. 12, pp. 1198-1210, December, 2009
Flow Separation for Fast and Robust Stereo Odometry
Michael Kaess, Kai Ni and Frank Dellaert

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, May, 2009
Evaluating the Performance of Map Optimization Algorithms
Edwin Olson and Michael Kaess

Miscellaneous, Workshop on Good Experimental Methodology in Robotics, January, 2009
iSAM: Incremental Smoothing and Mapping
Michael Kaess, Ananth Ranganathan and Frank Dellaert

Journal Article, Carnegie Mellon University, IEEE Trans. on Robotics, TRO, Vol. 24, No. 6, pp. 1365-1378, December, 2008
Place Recognition-based Fixed-Lag Smoothing for Environments with Unreliable GPS
Roozbeh Mottaghi, Michael Kaess, Ananth Ranganathan, Richard Roberts and Frank Dellaert

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, May, 2008
Fast 3D Pose Estimation With Out-of-Sequence Measurements
Ananth Ranganathan, Michael Kaess and Frank Dellaert

Conference Paper, Carnegie Mellon University, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, pp. 2486-2493, October, 2007
iSAM: Fast Incremental Smoothing and Mapping with Efficient Data Association
Michael Kaess, Ananth Ranganathan and Frank Dellaert

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, pp. 1670-1677, April, 2007
Fast Incremental Square Root Information Smoothing∗
Michael Kaess, Ananth Ranganathan and Frank Dellaert

Conference Paper, Carnegie Mellon University, Intl. Joint Conf. on Artificial Intelligence, IJCAI, Oral presentation acceptance ratio 15.7% (212 of 1353), pp. 2129-2134, January, 2007
Loopy SAM
Ananth Ranganathan, Michael Kaess and Frank Dellaert

Conference Paper, Carnegie Mellon University, Intl. Joint Conf. on Artificial Intelligence, IJCAI, Oral presentation acceptance ratio 15.7% (212 of 1353), pp. 2191-2196, January, 2007
Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing
Frank Dellaert and Michael Kaess

Journal Article, Carnegie Mellon University, Intl. J. of Robotics Research, IJRR, Vol. 25, No. 12, pp. 1181-1204, December, 2006
Visual SLAM with a Multi-Camera Rig
Michael Kaess and Frank Dellaert

Journal Article, Carnegie Mellon University, College of Computing, Georgia Institute of Technology - Technical Report GIT-GVU-06-06, February, 2006
A Markov Chain Monte Carlo Approach to Closing the Loop in SLAM
Michael Kaess and Frank Dellaert

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, pp. 645-650, April, 2005
MCMC-based Multiview Reconstruction of Piecewise Smooth Subdivision Curves with a Variable Number of Control Points
Michael Kaess, Rafal Zboinski and Frank Dellaert

Conference Paper, Carnegie Mellon University, Eur. Conf. on Computer Vision, ECCV, Acceptance ratio 34.2% (190 of 555), pp. 329-341, May, 2004
Reconstruction of Objects with Jagged Edges through Rao-Blackwellized Fitting of Piecewise Smooth Subdivision Curves
Michael Kaess and Frank Dellaert

Conference Paper, Carnegie Mellon University, Proceedings of the IEEE 1st International Workshop on Higher-Level Knowledge in 3D Modeling and Motion Analysis, pp. 39-47, October, 2003
Compact Encoding of Robot-Generated 3D Maps for Efficient Wireless Transmission
Michael Kaess, Ronald C. Arkin and Jarek Rossignac

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Advanced Robotics, ICAR, pp. 324-331, June, 2003
Learning Behavioral Parameterization Using Spatio-Temporal Case-Based Reasoning*
Maxim Likhachev, Michael Kaess and Ronald C. Arkin

Conference Paper, Carnegie Mellon University, IEEE Intl. Conf. on Robotics and Automation, ICRA, pp. 1282-1289, May, 2002
The Georgia Tech Yellow Jackets: A Marsupial Team for Urban Search and Rescue
Frank Dellaert, Tucker Balch, Michael Kaess, Ramprasad Ravichandran, Fernando Alegre, Marc Berhault, Robert McGuire, Ernest Merrill, Lilia Moshkina and Daniel Walker

Miscellaneous, AAAI Mobile Robot Competition, pp. 44-49, January, 2002
Mailing Address:

Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213

2017-11-22T09:59:49+00:00