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ORCIDMichael Kaess
Person information
- affiliation: Carnegie Mellon University, Robotics Institute, Pittsburgh, PA, USA
- affiliation (former): MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, USA
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2020 – today
- 2024
[i33]Mohamad Qadri, Kevin Zhang, Akshay Hinduja, Michael Kaess, Adithya Pediredla, Christopher A. Metzler:
AONeuS: A Neural Rendering Framework for Acoustic-Optical Sensor Fusion. CoRR abs/2402.03309 (2024)- [i32]Ziyuan Qu, Omkar Vengurlekar, Mohamad Qadri, Kevin Zhang, Michael Kaess, Christopher A. Metzler, Suren Jayasuriya, Adithya Pediredla:
Z-Splat: Z-Axis Gaussian Splatting for Camera-Sonar Fusion. CoRR abs/2404.04687 (2024) - 2023
- [j29]Wei Dong
, Yixing Lao, Michael Kaess, Vladlen Koltun:
ASH: A Modern Framework for Parallel Spatial Hashing in 3D Perception. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5417-5435 (2023) - [c102]Ming-Fang Chang, Akash Sharma, Michael Kaess, Simon Lucey:
Neural Radiance Fields with LiDAR Maps. ICCV 2023: 17868-17877 - [c101]Mohamad Qadri, Michael Kaess, Ioannis Gkioulekas:
Neural Implicit Surface Reconstruction using Imaging Sonar. ICRA 2023: 1040-1047 - [c100]Tianxiang Lin, Akshay Hinduja, Mohamad Qadri, Michael Kaess:
Conditional GANs for Sonar Image Filtering with Applications to Underwater Occupancy Mapping. ICRA 2023: 1048-1054 - [c99]Daniel McGann, John G. Rogers, Michael Kaess:
Robust Incremental Smoothing and Mapping (riSAM). ICRA 2023: 4157-4163 - [c98]Lipu Zhou, Jiacheng Liu, Fengguang Zhai, Pan Ai, Kefei Ren, Yinian Mao, Guoquan Huang, Ziyang Meng, Michael Kaess:
Efficient Bundle Adjustment for Coplanar Points and Lines. ICRA 2023: 8356-8363 - [i31]Brendon Forsgren, Ram Vasudevan, Michael Kaess, Timothy W. McLain, Joshua G. Mangelson:
Group-k consistent measurement set maximization via maximum clique over k-Uniform hypergraphs for robust multi-robot map merging. CoRR abs/2308.02674 (2023) - [i30]Mohamad Qadri, Michael Kaess:
Learning Observation Models with Incremental Non-Differentiable Graph Optimizers in the Loop for Robotics State Estimation. CoRR abs/2309.02525 (2023) - [i29]Mohamad Qadri, Zachary Manchester, Michael Kaess:
Learning Covariances for Estimation with Constrained Bilevel Optimization. CoRR abs/2309.09718 (2023) - [i28]Daniel McGann, Kyle Lassak, Michael Kaess:
Asynchronous Distributed Smoothing and Mapping via On-Manifold Consensus ADMM. CoRR abs/2310.12320 (2023) - [i27]Samiran Gode, Akshay Hinduja, Michael Kaess:
SONIC: Sonar Image Correspondence using Pose Supervised Learning for Imaging Sonars. CoRR abs/2310.15023 (2023) - [i26]Jui-Te Huang, Ruoyang Xu, Akshay Hinduja, Michael Kaess:
Multi-Radar Inertial Odometry for 3D State Estimation using mmWave Imaging Radar. CoRR abs/2311.08608 (2023) - [i25]Sudharshan Suresh, Haozhi Qi, Tingfan Wu, Taosha Fan, Luis Pineda, Mike Lambeta, Jitendra Malik, Mrinal Kalakrishnan, Roberto Calandra, Michael Kaess, Joseph Ortiz, Mustafa Mukadam:
Neural feels with neural fields: Visuo-tactile perception for in-hand manipulation. CoRR abs/2312.13469 (2023) - 2022
- [j28]Eric Dexheimer, Patrick Peluse, Jianhui Chen, James Pritts, Michael Kaess:
Information-Theoretic Online Multi-Camera Extrinsic Calibration. IEEE Robotics Autom. Lett. 7(2): 4757-4764 (2022) - [j27]Lipu Zhou, Guoquan Huang, Yinian Mao, Jincheng Yu, Shengze Wang, Michael Kaess:
$\mathcal {PLC}$-LiSLAM: LiDAR SLAM With Planes, Lines, and Cylinders. IEEE Robotics Autom. Lett. 7(3): 7163-7170 (2022) - [c97]Sudharshan Suresh, Zilin Si, Stuart Anderson, Michael Kaess, Mustafa Mukadam:
MidasTouch: Monte-Carlo inference over distributions across sliding touch. CoRL 2022: 319-331 - [c96]Ming-Fang Chang, Yipu Zhao, Rajvi Shah, Jakob J. Engel, Michael Kaess, Simon Lucey:
Long-term Visual Map Sparsification with Heterogeneous GNN. CVPR 2022: 2396-2405 - [c95]Paloma Sodhi, Michael Kaess, Mustafa Mukadam, Stuart Anderson:
PatchGraph: In-hand tactile tracking with learned surface normals. ICRA 2022: 2164-2170 - [c94]Easton R. Potokar, Spencer Ashford, Michael Kaess, Joshua G. Mangelson:
HoloOcean: An Underwater Robotics Simulator. ICRA 2022: 3040-3046 - [c93]Sudharshan Suresh, Zilin Si, Joshua G. Mangelson, Wenzhen Yuan, Michael Kaess:
ShapeMap 3-D: Efficient shape mapping through dense touch and vision. ICRA 2022: 7073-7080 - [c92]Lipu Zhou, Guoquan Huang, Yinian Mao, Shengze Wang, Michael Kaess:
EDPLVO: Efficient Direct Point-Line Visual Odometry. ICRA 2022: 7559-7565 - [c91]Yehonathan Litman, Daniel McGann, Eric Dexheimer, Michael Kaess:
GPS-Denied Global Visual-Inertial Ground Vehicle State Estimation via Image Registration. ICRA 2022: 8178-8184 - [c90]Brendon Forsgren, Ram Vasudevan, Michael Kaess, Timothy W. McLain, Joshua G. Mangelson:
Group-k Consistent Measurement Set Maximization for Robust Outlier Detection. IROS 2022: 4849-4856 - [c89]Akshay Hinduja, Yunsik Ohm, Jiahe Liao, Carmel Majidi, Michael Kaess:
Acoustic Localization and Communication Using a MEMS Microphone for Low-cost and Low-power Bio-inspired Underwater Robots. IROS 2022: 5470-5477 - [c88]Mohamad Qadri, Paloma Sodhi, Joshua G. Mangelson, Frank Dellaert, Michael Kaess:
InCOpt: Incremental Constrained Optimization using the Bayes Tree. IROS 2022: 6381-6388 - [c87]Easton R. Potokar, Kalliyan Lay, Kalin Norman, Derek Benham, Tracianne B. Neilsen, Michael Kaess, Joshua G. Mangelson:
HoloOcean: Realistic Sonar Simulation. IROS 2022: 8450-8456 - [c86]Ruoyang Xu, Wei Dong, Akash Sharma, Michael Kaess:
Learned Depth Estimation of 3D Imaging Radar for Indoor Mapping. IROS 2022: 13260-13267 - [i24]Ming-Fang Chang, Yipu Zhao, Rajvi Shah, Jakob J. Engel, Michael Kaess, Simon Lucey:
Long-term Visual Map Sparsification with Heterogeneous GNN. CoRR abs/2203.15182 (2022) - [i23]Brendon Forsgren, Ram Vasudevan, Michael Kaess, Timothy W. McLain, Joshua G. Mangelson:
Group-k Consistent Measurement Set Maximization for Robust Outlier Detection. CoRR abs/2209.02658 (2022) - [i22]Mohamad Qadri, Michael Kaess, Ioannis Gkioulekas:
Neural Implicit Surface Reconstruction using Imaging Sonar. CoRR abs/2209.08221 (2022) - [i21]Tianxiang Lin, Akshay Hinduja, Mohamad Qadri, Michael Kaess:
Conditional GANs for Sonar Image Filtering with Applications to Underwater Occupancy Mapping. CoRR abs/2209.11757 (2022) - [i20]Daniel McGann, John G. Rogers III, Michael Kaess:
Robust Incremental Smoothing and Mapping (riSAM). CoRR abs/2209.14359 (2022) - [i19]Akshay Hinduja, Yunsik Ohm, Jiahe Liao, Carmel Majidi, Michael Kaess:
Acoustic Localization and Communication Using a MEMS Microphone for Low-cost and Low-power Bio-inspired Underwater Robots. CoRR abs/2210.01089 (2022) - [i18]Bardienus Pieter Duisterhof, Yaoyu Hu, Si Heng Teng, Michael Kaess, Sebastian A. Scherer:
TartanCalib: Iterative Wide-Angle Lens Calibration using Adaptive SubPixel Refinement of AprilTags. CoRR abs/2210.02511 (2022) - [i17]Sudharshan Suresh, Zilin Si, Stuart Anderson, Michael Kaess, Mustafa Mukadam:
MidasTouch: Monte-Carlo inference over distributions across sliding touch. CoRR abs/2210.14210 (2022) - 2021
- [j26]Lipu Zhou, Daniel Koppel, Michael Kaess:
A Complete, Accurate and Efficient Solution for the Perspective-N-Line Problem. IEEE Robotics Autom. Lett. 6(2): 699-706 (2021) - [j25]Lipu Zhou, Daniel Koppel, Michael Kaess:
LiDAR SLAM With Plane Adjustment for Indoor Environment. IEEE Robotics Autom. Lett. 6(4): 7073-7080 (2021) - [j24]Lipu Zhou, Shengze Wang, Michael Kaess:
DPLVO: Direct Point-Line Monocular Visual Odometry. IEEE Robotics Autom. Lett. 6(4): 7113-7120 (2021) - [c85]Paloma Sodhi, Eric Dexheimer, Mustafa Mukadam, Stuart Anderson, Michael Kaess:
LEO: Learning Energy-based Models in Factor Graph Optimization. CoRL 2021: 234-244 - [c84]Lipu Zhou, Shengze Wang, Michael Kaess:
π-LSAM: LiDAR Smoothing and Mapping With Planes. ICRA 2021: 5751-5757 - [c83]Montiel Abello, Joshua G. Mangelson, Michael Kaess:
A Graph-Based Method for Joint Instance Segmentation of Point Clouds and Image Sequences. ICRA 2021: 9565-9571 - [c82]Sudharshan Suresh, Maria Bauzá, Kuan-Ting Yu, Joshua G. Mangelson, Alberto Rodriguez, Michael Kaess:
Tactile SLAM: Real-time inference of shape and pose from planar pushing. ICRA 2021: 11322-11328 - [c81]Akash Sharma, Wei Dong, Michael Kaess:
Compositional and Scalable Object SLAM. ICRA 2021: 11626-11632 - [c80]Ming-Fang Chang, Joshua G. Mangelson, Michael Kaess, Simon Lucey:
HyperMap: Compressed 3D Map for Monocular Camera Registration. ICRA 2021: 11739-11745 - [c79]Paloma Sodhi, Michael Kaess, Mustafa Mukadam, Stuart Anderson:
Learning Tactile Models for Factor Graph-based Estimation. ICRA 2021: 13686-13692 - [c78]Alexander Baikovitz, Paloma Sodhi, Michael Dille, Michael Kaess:
Ground Encoding: Learned Factor Graph-based Models for Localizing Ground Penetrating Radar. IROS 2021: 5476-5483 - [c77]Ming-Fang Chang, Wei Dong, Joshua G. Mangelson, Michael Kaess, Simon Lucey:
Map Compressibility Assessment for LiDAR Registration. IROS 2021: 5560-5567 - [c76]Dehann Fourie, Antonio Terán Espinoza, Michael Kaess, John J. Leonard:
Characterizing Marginalization and Incremental Operations on the Bayes Tree. WAFR 2021: 227-242 - [i16]Alexander Baikovitz, Paloma Sodhi, Michael Dille, Michael Kaess:
Ground Encoding: Learned Factor Graph-based Models for Localizing Ground Penetrating Radar. CoRR abs/2103.15317 (2021) - [i15]Alexander Baikovitz, Paloma Sodhi, Michael Dille, Michael Kaess:
CMU-GPR Dataset: Ground Penetrating Radar Dataset for Robot Localization and Mapping. CoRR abs/2107.07606 (2021) - [i14]Paloma Sodhi, Eric Dexheimer, Mustafa Mukadam, Stuart Anderson, Michael Kaess:
LEO: Learning Energy-based Models in Graph Optimization. CoRR abs/2108.02274 (2021) - [i13]Sudharshan Suresh, Zilin Si, Joshua G. Mangelson, Wenzhen Yuan, Michael Kaess:
Efficient shape mapping through dense touch and vision. CoRR abs/2109.09884 (2021) - [i12]Wei Dong, Yixing Lao, Michael Kaess, Vladlen Koltun:
ASH: A Modern Framework for Parallel Spatial Hashing in 3D Perception. CoRR abs/2110.00511 (2021) - [i11]Paloma Sodhi, Michael Kaess, Mustafa Mukadam, Stuart Anderson:
PatchGraph: In-hand tactile tracking with learned surface normals. CoRR abs/2111.07524 (2021) - [i10]Wei Dong, Kwonyoung Ryu, Michael Kaess, Jaesik Park:
Real-time Registration and Reconstruction with Cylindrical LiDAR Images. CoRR abs/2112.02779 (2021) - 2020
- [j23]Lipu Zhou, Michael Kaess:
Windowed Bundle Adjustment Framework for Unsupervised Learning of Monocular Depth Estimation With U-Net Extension and Clip Loss. IEEE Robotics Autom. Lett. 5(2): 3283-3290 (2020) - [c75]Paloma Sodhi, Sanjiban Choudhury, Joshua G. Mangelson, Michael Kaess:
ICS: Incremental Constrained Smoothing for State Estimation. ICRA 2020: 279-285 - [c74]Lipu Zhou, Shengze Wang, Michael Kaess:
A Fast and Accurate Solution for Pose Estimation from 3D Correspondences. ICRA 2020: 1308-1314 - [c73]Sudharshan Suresh, Paloma Sodhi, Joshua G. Mangelson, David Wettergreen, Michael Kaess:
Active SLAM using 3D Submap Saliency for Underwater Volumetric Exploration. ICRA 2020: 3132-3138 - [c72]Eric Westman, Ioannis Gkioulekas, Michael Kaess:
A Volumetric Albedo Framework for 3D Imaging Sonar Reconstruction. ICRA 2020: 9645-9651 - [c71]Vaibhav K. Viswanathan, Eric Dexheimer, Guanrui Li, Giuseppe Loianno, Michael Kaess, Sebastian A. Scherer:
Efficient Trajectory Library Filtering for Quadrotor Flight in Unknown Environments. IROS 2020: 2510-2517 - [c70]Joshua Jaekel, Joshua G. Mangelson, Sebastian A. Scherer, Michael Kaess:
A Robust Multi-Stereo Visual-Inertial Odometry Pipeline. IROS 2020: 4623-4630 - [c69]Eric Dexheimer, Joshua G. Mangelson, Sebastian A. Scherer, Michael Kaess:
Efficient Multiresolution Scrolling Grid for Stereo Vision-based MAV Obstacle Avoidance. IROS 2020: 4758-4765 - [c68]Ming Hsiao, Joshua G. Mangelson, Sudharshan Suresh, Christian Debrunner, Michael Kaess:
ARAS: Ambiguity-aware Robust Active SLAM based on Multi-hypothesis State and Map Estimations. IROS 2020: 5037-5044 - [c67]Eric Westman, Ioannis Gkioulekas, Michael Kaess:
A Theory of Fermat Paths for 3D Imaging Sonar Reconstruction. IROS 2020: 5082-5088 - [c66]Lipu Zhou, Daniel Koppel, Hui Ju, Frank Steinbrücker, Michael Kaess:
An Efficient Planar Bundle Adjustment Algorithm. ISMAR 2020: 136-145 - [i9]Lipu Zhou, Daniel Koppel, Hui Ju, Frank Steinbrücker, Michael Kaess:
An Efficient Planar Bundle Adjustment Algorithm. CoRR abs/2006.00187 (2020) - [i8]Akash Sharma, Wei Dong, Michael Kaess:
Compositional Scalable Object SLAM. CoRR abs/2011.02658 (2020) - [i7]Sudharshan Suresh, Maria Bauzá, Kuan-Ting Yu, Joshua G. Mangelson, Alberto Rodriguez, Michael Kaess:
Tactile SLAM: Real-time inference of shape and pose from planar pushing. CoRR abs/2011.07044 (2020) - [i6]Paloma Sodhi, Michael Kaess, Mustafa Mukadam, Stuart Anderson:
Learning Tactile Models for Factor Graph-based State Estimation. CoRR abs/2012.03768 (2020)
2010 – 2019
- 2019
- [j22]Shohin Mukherjee, Michael Kaess, Joseph N. Martel, Cameron N. Riviere:
EyeSAM: graph-based localization and mapping of retinal vasculature during intraocular microsurgery. Int. J. Comput. Assist. Radiol. Surg. 14(5): 819-828 (2019) - [j21]Sudharshan Suresh, Eric Westman, Michael Kaess:
Through-Water Stereo SLAM With Refraction Correction for AUV Localization. IEEE Robotics Autom. Lett. 4(2): 692-699 (2019) - [c65]Lipu Zhou, Yi Yang, Montiel Abello, Michael Kaess:
A Robust and Efficient Algorithm for the PnL Problem Using Algebraic Distance to Approximate the Reprojection Distance. AAAI 2019: 9307-9315 - [c64]Ming Hsiao, Michael Kaess:
MH-iSAM2: Multi-hypothesis iSAM using Bayes Tree and Hypo-tree. ICRA 2019: 1274-1280 - [c63]Yi Yang, Wei Dong, Michael Kaess:
Surfel-Based Dense RGB-D Reconstruction With Global And Local Consistency. ICRA 2019: 5238-5244 - [c62]Ratnesh Madaan, Michael Kaess, Sebastian A. Scherer:
Multi-view Reconstruction of Wires using a Catenary Model. ICRA 2019: 5657-5664 - [c61]Zimo Li, Prakruti C. Gogia, Michael Kaess:
Dense Surface Reconstruction from Monocular Vision and LiDAR. ICRA 2019: 6905-6911 - [c60]Akshay Hinduja, Bing-Jui Ho, Michael Kaess:
Degeneracy-Aware Factors with Applications to Underwater SLAM. IROS 2019: 1293-1299 - [c59]Lipu Zhou, Michael Kaess:
An Efficient and Accurate Algorithm for the Perspecitve-n-Point Problem. IROS 2019: 6245-6252 - [c58]Wei Dong, Jaesik Park, Yi Yang, Michael Kaess:
GPU Accelerated Robust Scene Reconstruction. IROS 2019: 7863-7870 - [c57]Paloma Sodhi, Bing-Jui Ho, Michael Kaess:
Online and Consistent Occupancy Grid Mapping for Planning in Unknown Environments. IROS 2019: 7879-7886 - [c56]Pedro V. Teixeira, Dehann Fourie, Michael Kaess, John J. Leonard:
Dense, Sonar-based Reconstruction of Underwater Scenes. IROS 2019: 8060-8066 - [c55]Eric Westman, Michael Kaess:
Wide Aperture Imaging Sonar Reconstruction using Generative Models. IROS 2019: 8067-8074 - [i5]Lipu Zhou, Shengze Wang, Jiamin Ye, Michael Kaess:
Do not Omit Local Minimizer: a Complete Solution for Pose Estimation from 3D Correspondences. CoRR abs/1904.01759 (2019) - 2018
- [j20]Jie Li, Michael Kaess, Ryan M. Eustice, Matthew Johnson-Roberson:
Pose-Graph SLAM Using Forward-Looking Sonar. IEEE Robotics Autom. Lett. 3(3): 2330-2337 (2018) - [c54]Lipu Zhou, Jiamin Ye, Michael Kaess:
A Stable Algebraic Camera Pose Estimation for Minimal Configurations of 2D/3D Point and Line Correspondences. ACCV (4) 2018: 273-288 - [c53]Eric Westman, Akshay Hinduja, Michael Kaess:
Feature-Based SLAM for Imaging Sonar with Under-Constrained Landmarks. ICRA 2018: 1-9 - [c52]Ming Hsiao, Eric Westman, Michael Kaess:
Dense Planar-Inertial SLAM with Structural Constraints. ICRA 2018: 6521-6528 - [c51]Jerry Hsiung, Ming Hsiao, Eric Westman, Rafael Valencia, Michael Kaess:
Information Sparsification in Visual-Inertial Odometry. IROS 2018: 1146-1153 - [c50]Pedro V. Teixeira, Franz S. Hover, John J. Leonard, Michael Kaess:
Multibeam Data Processing for Underwater Mapping. IROS 2018: 1877-1884 - [c49]Bing-Jui Ho, Paloma Sodhi, Pedro Teixeira, Ming Hsiao, Tushar Kusnur, Michael Kaess:
Virtual Occupancy Grid Map for Submap-based Pose Graph SLAM and Planning in 3D Environments. IROS 2018: 2175-2182 - [c48]Lipu Zhou, Zimo Li, Michael Kaess:
Automatic Extrinsic Calibration of a Camera and a 3D LiDAR Using Line and Plane Correspondences. IROS 2018: 5562-5569 - [i4]Lipu Zhou, Jiamin Ye, Montiel Abello, Shengze Wang, Michael Kaess:
Unsupervised Learning of Monocular Depth Estimation with Bundle Adjustment, Super-Resolution and Clip Loss. CoRR abs/1812.03368 (2018) - 2017
- [j19]Ji Zhang, Michael Kaess, Sanjiv Singh:
A real-time method for depth enhanced visual odometry. Auton. Robots 41(1): 31-43 (2017) - [j18]Frank Dellaert, Michael Kaess:
Factor Graphs for Robot Perception. Found. Trends Robotics 6(1-2): 1-139 (2017) - [j17]Hatem Alismail, Michael Kaess, Brett Browning, Simon Lucey:
Direct Visual Odometry in Low Light Using Binary Descriptors. IEEE Robotics Autom. Lett. 2(2): 444-451 (2017) - [c47]Shuangli Zhang, Weijian Xie, Guofeng Zhang, Hujun Bao, Michael Kaess:
Robust stereo matching with surface normal prediction. ICRA 2017: 2540-2547 - [c46]Michael C. Koval, Matthew Klingensmith, Siddhartha S. Srinivasa, Nancy S. Pollard, Michael Kaess:
The manifold particle filter for state estimation on high-dimensional implicit manifolds. ICRA 2017: 4673-4680 - [c45]Ming Hsiao, Eric Westman, Guofeng Zhang, Michael Kaess:
Keyframe-based dense planar SLAM. ICRA 2017: 5110-5117 - [c44]Puneet Puri, Daoyuan Jia, Michael Kaess:
GravityFusion: Real-time dense mapping without pose graph using deformation and orientation. IROS 2017: 6506-6513 - [i3]Shichao Yang, Yu Song, Michael Kaess, Sebastian A. Scherer:
Pop-up SLAM: Semantic Monocular Plane SLAM for Low-texture Environments. CoRR abs/1703.07334 (2017) - [i2]Haomin Liu, Chen Li, Guojun Chen, Guofeng Zhang, Michael Kaess, Hujun Bao:
Robust Keyframe-based Dense SLAM with an RGB-D Camera. CoRR abs/1711.05166 (2017) - 2016
- [j16]Matthew Klingensmith, Siddartha S. Sirinivasa, Michael Kaess:
Articulated Robot Motion for Simultaneous Localization and Mapping (ARM-SLAM). IEEE Robotics Autom. Lett. 1(2): 1156-1163 (2016) - [c43]Ji Zhang, Michael Kaess, Sanjiv Singh:
On degeneracy of optimization-based state estimation problems. ICRA 2016: 809-816 - [c42]Shichao Yang, Yu Song, Michael Kaess, Sebastian A. Scherer:
Pop-up SLAM: Semantic monocular plane SLAM for low-texture environments. IROS 2016: 1222-1229 - [c41]Tiffany A. Huang, Michael Kaess:
Incremental data association for acoustic structure from motion. IROS 2016: 1334-1341 - [c40]Garrett Hemann, Sanjiv Singh, Michael Kaess:
Long-range GPS-denied aerial inertial navigation with LIDAR localization. IROS 2016: 1659-1666 - [c39]Dehann Fourie, John J. Leonard, Michael Kaess:
A nonparametric belief solution to the Bayes tree. IROS 2016: 2189-2196 - [c38]Pedro V. Teixeira, Michael Kaess, Franz S. Hover, John J. Leonard:
Underwater inspection using sonar-based volumetric submaps. IROS 2016: 4288-4295 - [i1]Matthew Klingensmith, Michael C. Koval, Siddhartha S. Srinivasa, Nancy S. Pollard, Michael Kaess:
The Manifold Particle Filter for State Estimation on High-dimensional Implicit Manifolds. CoRR abs/1604.07224 (2016) - 2015
- [j15]Thomas Whelan, Michael Kaess, Hordur Johannsson, Maurice F. Fallon, John J. Leonard, John McDonald:
Real-time large-scale dense RGB-D SLAM with volumetric fusion. Int. J. Robotics Res. 34(4-5): 598-626 (2015) - [j14]Guoquan Huang, Michael Kaess, John J. Leonard:
Consistent unscented incremental smoothing for multi-robot cooperative target tracking. Robotics Auton. Syst. 69: 52-67 (2015) - [c37]Paul Ozog, Giancarlo Troni, Michael Kaess, Ryan M. Eustice, Matthew Johnson-Roberson:
Building 3D mosaics from an Autonomous Underwater Vehicle, Doppler velocity log, and 2D imaging sonar. ICRA 2015: 1137-1143 - [c36]Michael Kaess:
Simultaneous localization and mapping with infinite planes. ICRA 2015: 4605-4611 - [c35]Tiffany A. Huang, Michael Kaess:
Towards acoustic structure from motion for imaging sonar. IROS 2015: 758-765 - [c34]Hsueh-Cheng Wang, Chelsea Finn, Liam Paull, Michael Kaess, Ruth Rosenholtz, Seth J. Teller, John J. Leonard:
Bridging text spotting and SLAM with junction features. IROS 2015: 3701-3708 - 2014
- [j13]Stephen Williams, Vadim Indelman, Michael Kaess, Richard Roberts, John J. Leonard, Frank Dellaert:
Concurrent filtering and smoothing: A parallel architecture for real-time navigation and full smoothing. Int. J. Robotics Res. 33(12): 1544-1568 (2014) - [j12]David M. Rosen, Michael Kaess, John J. Leonard:
RISE: An Incremental Trust-Region Method for Robust Online Sparse Least-Squares Estimation. IEEE Trans. Robotics 30(5): 1091-1108 (2014) - [j11]Nicholas Carlevaris-Bianco, Michael Kaess, Ryan M. Eustice:
Generic Node Removal for Factor-Graph SLAM. IEEE Trans. Robotics 30(6): 1371-1385 (2014) - [c33]Guoquan Huang, Michael Kaess, John J. Leonard:
Towards consistent visual-inertial navigation. ICRA 2014: 4926-4933 - [c32]Ross Finman, Thomas Whelan, Michael Kaess, John J. Leonard:
Efficient incremental map segmentation in dense RGB-D maps. ICRA 2014: 5488-5494 - [c31]Ji Zhang, Michael Kaess, Sanjiv Singh:
Real-time depth enhanced monocular odometry. IROS 2014: 4973-4980 - 2013
- [j10]Maurice F. Fallon, Hordur Johannsson, Michael Kaess, John J. Leonard:
The MIT Stata Center dataset. Int. J. Robotics Res. 32(14): 1695-1699 (2013) - [j9]Allen Wu, Eric N. Johnson, Michael Kaess, Frank Dellaert, Girish Chowdhary:
Autonomous Flight in GPS-Denied Environments Using Monocular Vision and Inertial Sensors. J. Aerosp. Inf. Syst. 10(4): 172-186 (2013) - [j8]Vadim Indelman, Stephen Williams, Michael Kaess, Frank Dellaert:
Information fusion in navigation systems via factor graph based incremental smoothing. Robotics Auton. Syst. 61(8): 721-738 (2013) - [j7]John McDonald, Michael Kaess, Cesar Dario Cadena Lerma, José Neira, John J. Leonard:
Real-time 6-DOF multi-session visual SLAM over large-scale environments. Robotics Auton. Syst. 61(10): 1144-1158 (2013) - [c30]Guoquan Huang, Michael Kaess, John J. Leonard:
Consistent sparsification for graph optimization. ECMR 2013: 150-157 - [c29]Ross Finman, Thomas Whelan, Michael Kaess, John J. Leonard:
Toward lifelong object segmentation from change detection in dense RGB-D maps. ECMR 2013: 178-185 - [c28]Guoquan Huang, Robert Truax, Michael Kaess, John J. Leonard:
Unscented iSAM: A consistent incremental solution to cooperative localization and target tracking. ECMR 2013: 248-254 - [c27]Mark VanMiddlesworth, Michael Kaess, Franz Hover, John J. Leonard:
Mapping 3D Underwater Environments with Smoothed Submaps. FSR 2013: 17-30 - [c26]Guoquan Huang, Michael Kaess, John J. Leonard, Stergios I. Roumeliotis:
Analytically-selected multi-hypothesis incremental MAP estimation. ICASSP 2013: 6481-6485 - [c25]Hordur Johannsson, Michael Kaess, Maurice F. Fallon, John J. Leonard:
Temporally scalable visual SLAM using a reduced pose graph. ICRA 2013: 54-61 - [c24]David M. Rosen, Michael Kaess, John J. Leonard:
Robust incremental online inference over sparse factor graphs: Beyond the Gaussian case. ICRA 2013: 1025-1032 - [c23]Thomas Whelan, Hordur Johannsson, Michael Kaess, John J. Leonard, John McDonald:
Robust real-time visual odometry for dense RGB-D mapping. ICRA 2013: 5724-5731 - [c22]Thomas Whelan, Michael Kaess, John J. Leonard, John McDonald:
Deformation-based loop closure for large scale dense RGB-D SLAM. IROS 2013: 548-555 - 2012
- [j6]Michael Kaess, Hordur Johannsson, Richard Roberts, Viorela Ila, John J. Leonard, Frank Dellaert:
iSAM2: Incremental smoothing and mapping using the Bayes tree. Int. J. Robotics Res. 31(2): 216-235 (2012) - [j5]Franz S. Hover, Ryan M. Eustice, Ayoung Kim, Brendan J. Englot, Hordur Johannsson, Michael Kaess, John J. Leonard:
Advanced perception, navigation and planning for autonomous in-water ship hull inspection. Int. J. Robotics Res. 31(12): 1445-1464 (2012) - [c21]Michael Kaess, Stephen Williams, Vadim Indelman, Richard Roberts, John J. Leonard, Frank Dellaert:
Concurrent filtering and smoothing. FUSION 2012: 1300-1307 - [c20]Vadim Indelman, Stephen Williams, Michael Kaess, Frank Dellaert:
Factor graph based incremental smoothing in inertial navigation systems. FUSION 2012: 2154-2161 - [c19]David M. Rosen, Michael Kaess, John J. Leonard:
An incremental trust-region method for Robust online sparse least-squares estimation. ICRA 2012: 1262-1269 - [c18]Aisha Walcott-Bryant, Michael Kaess, Hordur Johannsson, John J. Leonard:
Dynamic pose graph SLAM: Long-term mapping in low dynamic environments. IROS 2012: 1871-1878 - 2011
- [c17]John McDonald, Michael Kaess, Cesar Dario Cadena Lerma, José Neira, John J. Leonard:
6-DOF Multi-session Visual SLAM using Anchor Nodes. ECMR 2011: 69-76 - [c16]Maurice F. Fallon, Michael Kaess, Hordur Johannsson, John J. Leonard:
Efficient AUV navigation fusing acoustic ranging and side-scan sonar. ICRA 2011: 2398-2405 - [c15]Michael Kaess, Hordur Johannsson, Richard Roberts, Viorela Ila, John J. Leonard, Frank Dellaert:
iSAM2: Incremental smoothing and mapping with fluid relinearization and incremental variable reordering. ICRA 2011: 3281-3288 - 2010
- [j4]Michael Kaess, Frank Dellaert:
Probabilistic structure matching for visual SLAM with a multi-camera rig. Comput. Vis. Image Underst. 114(2): 286-296 (2010) - [c14]Been Kim, Michael Kaess, Luke Fletcher, John J. Leonard, Abraham Bachrach, Nicholas Roy, Seth J. Teller:
Multiple relative pose graphs for robust cooperative mapping. ICRA 2010: 3185-3192 - [c13]Hordur Johannsson, Michael Kaess, Brendan J. Englot, Franz Hover, John J. Leonard:
Imaging sonar-aided navigation for autonomous underwater harbor surveillance. IROS 2010: 4396-4403 - [c12]Michael Kaess, Viorela Ila, Richard Roberts, Frank Dellaert:
The Bayes Tree: An Algorithmic Foundation for Probabilistic Robot Mapping. WAFR 2010: 157-173
2000 – 2009
- 2009
- [j3]Michael Kaess, Frank Dellaert:
Covariance recovery from a square root information matrix for data association. Robotics Auton. Syst. 57(12): 1198-1210 (2009) - [c11]Michael Kaess, Kai Ni, Frank Dellaert:
Flow separation for fast and robust stereo odometry. ICRA 2009: 3539-3544 - 2008
- [j2]Michael Kaess, Ananth Ranganathan, Frank Dellaert:
iSAM: Incremental Smoothing and Mapping. IEEE Trans. Robotics 24(6): 1365-1378 (2008) - [c10]Roozbeh Mottaghi, Michael Kaess, Ananth Ranganathan, Richard Roberts, Frank Dellaert:
Place recognition-based fixed-lag smoothing for environments with unreliable GPS. ICRA 2008: 1862-1867 - 2007
- [c9]Michael Kaess, Ananth Ranganathan, Frank Dellaert:
iSAM: Fast Incremental Smoothing and Mapping with Efficient Data Association. ICRA 2007: 1670-1677 - [c8]Michael Kaess, Ananth Ranganathan, Frank Dellaert:
Fast Incremental Square Root Information Smoothing. IJCAI 2007: 2129-2134 - [c7]Ananth Ranganathan, Michael Kaess, Frank Dellaert:
Loopy SAM. IJCAI 2007: 2191-2196 - [c6]Ananth Ranganathan, Michael Kaess, Frank Dellaert:
Fast 3D pose estimation with out-of-sequence measurements. IROS 2007: 2486-2493 - 2006
- [j1]Frank Dellaert, Michael Kaess:
Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing. Int. J. Robotics Res. 25(12): 1181-1203 (2006) - 2005
- [c5]Michael Kaess, Frank Dellaert:
A Markov Chain Monte Carlo Approach to Closing the Loop in SLAM. ICRA 2005: 643-648 - 2004
- [c4]Michael Kaess, Rafal Zboinski, Frank Dellaert:
MCMC-Based Multiview Reconstruction of Piecewise Smooth Subdivision Curves with a Variable Number of Control Points. ECCV (3) 2004: 329-341 - 2003
- [c3]Michael Kaess, Frank Dellaert:
Reconstruction of Objects with Jagged Edges through Rao-Blackwellized Fitting of Piecewise Smooth Subdivision Curves. HLK 2003: 39-47 - 2002
- [c2]Maxim Likhachev, Michael Kaess, Ronald C. Arkin:
Learning Behavioral Parameterization using Spatio-Temporal Case-Based Reasoning. ICRA 2002: 1282-1289 - [c1]Frank Dellaert, Tucker R. Balch, Michael Kaess, Ram Ravichandran, Fernando Alegre, Marc Berhault, Robert McGuire, Ernest Merrill, Lilia V. Moshkina, Daniel Walker:
The Georgia Tech Yellow Jackets: A Marsupial Team for Urban Search and Rescue. AAAI Mobile Robot Competition 2002: 44-49
Coauthor Index
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