Publications

Dissertation

[1]

Incremental Smoothing and Mapping
by M. Kaess.
Ph.D. dissertation, Georgia Institute of Technology, Dec. 2008.
Details. Download: PDF.

Journal papers

[2]

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, May 2023, pp. 5417-5435.
Details. Download: PDF.

[3]

PLC-LiSLAM: LiDAR SLAM with Planes, Lines and Cylinders
by L. Zhou, G. Huang, Y. Mao, J. Yu, S. Wang, and M. Kaess.
IEEE Robotics and Automation Letters, RA-L, vol. 7, no. 3, July 2022, pp. 7163-7170. Presented at IROS 2022.
Details. Download: PDF.

[4]

Resilient and Modular Subterranean Exploration with a Team of Roving and Flying Robots
by S. Scherer, V. Agrawal, G. Best, C. Cao, K. Cujic, R. Darnley, R. DeBortoli, E. Dexheimer, B. Drozd, R. Garg, I. Higgins, J. Keller, D. Kohanbash, L. Nogueira, R. Pradhan, M. Tatum, V.K. Viswanathan, S. Willits, S. Zhao, H. Zhu, D. Abad, T. Angert, G. Armstrong, R. Boirum, A. Dongare, M. Dworman, S. Hu, J. Jaekel, R. Ji, A. Lai, Y. Hsuan Lee, A. Luong, J. Mangelson, J. Maier, J. Picard, K. Pluckter, A. Saba, M. Saroya, E. Scheide, N. Shoemaker-Trejo, J. Spisak, J. Teza, F. Yang, A. Wilson, H. Zhang, H. Choset, M. Kaess, A. Rowe, S. Singh, J. Zhang, G.A. Hollinger, and M. Travers.
J. of Field Robotics (JFR), vol. 2, May 2022, pp. 678-734.
Details. Download: PDF.

[5]

Information-Theoretic Online Multi-Camera Extrinsic Calibration
by E. Dexheimer, P. Peluse, J. Chen, J. Pritts, and M. Kaess.
IEEE Robotics and Automation Letters, RA-L, vol. 7, no. 2, Apr. 2022, pp. 4757-4764. Presented at ICRA 2022.
Details. Download: PDF.

[6]

LiDAR SLAM with Plane Adjustment for Indoor Environment
by L. Zhou, D. Koppel, and M. Kaess.
IEEE Robotics and Automation Letters, RA-L, vol. 6, no. 4, Oct. 2021, pp. 7073-7080. Presented at IROS 2021.
Details. Download: PDF.

[7]

DPLVO: Direct Point-Line Monocular Visual Odometry
by L. Zhou, S. Wang, and M. Kaess.
IEEE Robotics and Automation Letters, RA-L, vol. 6, no. 4, Oct. 2021, pp. 7113-7120. Presented at IROS 2021.
Details. Download: PDF.

[8]

A Complete, Accurate and Efficient Solution for the Perspective-n-Line Problem
by L. Zhou, D. Koppel, and M. Kaess.
IEEE Robotics and Automation Letters, RA-L, vol. 6, no. 2, Apr. 2021, pp. 699-706. Presented at ICRA 2021.
Details. Download: PDF.

[9]

Degeneracy-aware Imaging Sonar Simultaneous Localization and Mapping
by E. Westman and M. Kaess.
IEEE J. of Oceanic Engineering (JOE), vol. 45, no. 4, Oct. 2020, pp. 1280-1294.
Details. Download: PDF.

[10]

Windowed Bundle Adjustment Framework for Unsupervised Learning of Monocular Depth Estimation with U-Net Extension and Clip Loss
by L. Zhou and M. Kaess.
IEEE Robotics and Automation Letters, RA-L, vol. 5, no. 2, Apr. 2020, pp. 3283-3290.
Details. Download: PDF.

[11]

EyeSAM: Graph-based Localization and Mapping of Retinal Vasculature during Intraocular Microsurgery
by S. Mukherjee, M. Kaess, J.N. Martel, and C.N. Riviere.
Intl. J. of Computer Assisted Radiology and Surgery (JCARS), vol. 14, no. 5, May 2019, pp. 819-828.
Details.

[12]

Through-water Stereo SLAM with Refraction Correction for AUV Localization
by S. Suresh, E. Westman, and M. Kaess.
IEEE Robotics and Automation Letters, RA-L, vol. 4, no. 2, Apr. 2019, pp. 692-699. Presented at ICRA 2019.
Details. Download: PDF.

[13]

Pose-graph SLAM using Forward-looking Sonar
by J. Li, M. Kaess, R.M. Eustice, and M. Johnson-Roberson.
IEEE Robotics and Automation Letters, RA-L, vol. 3, no. 3, July 2018, pp. 2330-2337. Presented at ICRA 2018.
Details. Download: PDF.

[14]

Factor Graphs for Robot Perception
by F. Dellaert and M. Kaess.
Foundations and Trends in Robotics, FNT, vol. 6, no. 1-2, Aug. 2017, pp. 1-139. http://dx.doi.org/10.1561/2300000043.
Details. Download: PDF.

[15]

Direct Visual Odometry in Low Light using Binary Descriptors
by H. Alismail, M. Kaess, B. Browning, and S. Lucey.
IEEE Robotics and Automation Letters, RA-L, vol. 2, no. 2, Apr. 2017, pp. 444-451. Presented at ICRA 2017.
Details. Download: PDF.

[16]

A Real-time Method for Depth Enhanced Monocular Odometry
by J. Zhang, M. Kaess, and S. Singh.
Autonomous Robots, AURO, vol. 41, no. 1, Jan. 2017, pp. 31-43.
Details. Download: PDF.

[17]

Articulated Robot Motion for Simultaneous Localization and Mapping (ARM-SLAM)
by M. Klingensmith, S.S. Srinivasa, and M. Kaess.
IEEE Robotics and Automation Letters, RA-L, vol. 1, no. 2, July 2016, pp. 1156-1163. Presented at ICRA 2016. Best vision paper finalist (one of five).
Details. Download: PDF.

[18]

Consistent Unscented Incremental Smoothing for Multi-robot Cooperative Target Tracking
by G. Huang, M. Kaess, and J.J. Leonard.
J. of Robotics and Autonomous Systems, RAS, vol. 69, July 2015, pp. 52-67.
Details. Download: PDF.

[19]

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.

[20]

Generic Factor-Based Node Removal: Enabling Long-Term SLAM
by N. Carlevaris-Bianco, M. Kaess, and R.M. Eustice.
IEEE Trans. on Robotics, TRO, vol. 30, no. 6, Dec. 2014, pp. 1371-1385.
Details. Download: PDF.

[21]

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.

[22]

Concurrent Filtering and Smoothing: A Parallel Architecture for Real-Time Navigation and Full Smoothing
by S. Williams, V. Indelman, M. Kaess, R. Roberts, J.J. Leonard, and F. Dellaert.
Intl. J. of Robotics Research, IJRR, vol. 33, no. 12, Oct. 2014, pp. 1544-1568.
Details. Download: PDF.

[23]

The MIT Stata Center Dataset
by M.F. Fallon, H. Johannsson, M. Kaess, and J.J. Leonard.
Intl. J. of Robotics Research, IJRR, vol. 32, no. 14, Dec. 2013, pp. 1695-1699.
Details. Download: PDF.

[24]

Real-time 6-DOF Multi-session Visual SLAM over Large Scale Environments
by J.B. McDonald, M. Kaess, C. Cadena, J. Neira, and J.J. Leonard.
J. of Robotics and Autonomous Systems, RAS, vol. 61, no. 10, Oct. 2013, pp. 1144-1158.
Details. Download: PDF.

[25]

Information Fusion in Navigation Systems via Factor Graph Based Incremental Smoothing
by V. Indelman, S. Williams, M. Kaess, and F. Dellaert.
J. of Robotics and Autonomous Systems, RAS, vol. 61, no. 8, Aug. 2013, pp. 721-738.
Details. Download: PDF.

[26]

Autonomous Flight in GPS-Denied Environments Using Monocular Vision and Inertial Sensors
by A.D. Wu, E.N. Johnson, M. Kaess, F. Dellaert, and G. Chowdhary.
AIAA J. of Aerospace Information Systems, JAIS, vol. 10, no. 4, Apr. 2013, pp. 172-186.
Details. Download: PDF.

[27]

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.

[28]

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, no. 2, Feb. 2012, pp. 216-235.
Details. Download: PDF.

[29]

Probabilistic Structure Matching for Visual SLAM with a Multi-Camera Rig
by M. Kaess and F. Dellaert.
Computer Vision and Image Understanding, CVIU, vol. 114, no. 2, Feb. 2010, pp. 286-296.
Details. Download: PDF.

[30]

Covariance Recovery from a Square Root Information Matrix for Data Association
by M. Kaess and F. Dellaert.
J. of Robotics and Autonomous Systems, RAS, vol. 57, no. 12, Dec. 2009, pp. 1198-1210.
Details. Download: PDF.

[31]

iSAM: Incremental Smoothing and Mapping
by M. Kaess, A. Ranganathan, and F. Dellaert.
IEEE Trans. on Robotics, TRO, vol. 24, no. 6, Dec. 2008, pp. 1365-1378.
Details. Download: PDF.

[32]

Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing
by F. Dellaert and M. Kaess.
Intl. J. of Robotics Research, IJRR, vol. 25, no. 12, Dec. 2006, pp. 1181-1204.
Details. Download: PDF.

Book chapter

[33]

Simultaneous Localization and Mapping in Marine Environments
by M.F. Fallon, H. Johannsson, M. Kaess, J. Folkesson, H. McClelland, B.J. Englot, F.S. Hover, and J. J. Leonard.
In Marine Robot Autonomy, (Mae L. Seto, ed.), 2013, pp. 329-372. https://doi.org/10.1007/978-1-4614-5659-9_8.
Details.

Peer-reviewed publications

[34]

Neural Radiance Field with LiDAR Maps
by M.-F. Chang, A. Sharma, M. Kaess, and S. Lucey.
In Proc. Intl. Conf. on Computer Vision, ICCV, (Paris, France), Oct. 2023.
Details. Download: PDF.

[35]

Robust Incremental Smoothing and Mapping (riSAM)
by D. McGann, J.G. Rogers III, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (London, UK), May 2023.
Details. Download: PDF.

[36]

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.
Details. Download: PDF.

[37]

Efficient Bundle Adjustment for Coplanar Points and Lines
by L. Zhou, J. Liu, P. Ai, F. Zhai, K. Ren, Z. Meng, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (London, UK), May 2023.
Details. Download: PDF.

[38]

Conditional GANs for Sonar Image Filtering with Applications to Underwater Occupancy Mapping
by T. Lin, A. Hinduja, M. Qadri, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (London, UK), May 2023.
Details. Download: PDF.

[39]

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.

[40]

InCOpt: Incremental Constrained Optimization using the Bayes Tree
by M. Qadri, P. Sodhi, J.G. Mangelson, F. Dellaert, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Kyoto, Japan), Oct. 2022.
Details. Download: PDF.

[41]

HoloOcean: Realistic Sonar Simulation
by E. Potokar, K. Lay, K. Norman, D. Benham, T. Neilsen, M. Kaess, and J.G. Mangelson.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Kyoto, Japan), Oct. 2022.
Details. Download: PDF.

[42]

Learned Depth Estimation of 3D Imaging Radar for Indoor Mapping
by R. Xu, W. Dong, A. Sharma, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Kyoto, Japan), Oct. 2022.
Details. Download: PDF.

[43]

Group-k Consistent Measurement Set Maximization for Robust Outlier Detection
by B. Forsgren, R. Vasudevan, M. Kaess, T.W. McLain, and J.G. Mangelson.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Kyoto, Japan), Oct. 2022.
Details. Download: PDF.

[44]

Acoustic Localization and Communication Using a MEMS Microphone for Low-cost and Low-power Bio-inspired Underwater Robots
by A. Hinduja, Y. Ohm, J. Liao, C. Majidi, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Kyoto, Japan), Oct. 2022.
Details. Download: PDF.

[45]

Long-term Visual Map Sparsification with Heterogeneous GNN
by M.-F. Chang, Y. Zhao, R. Shah, J.J. Engel, M. Kaess, and S. Lucey.
In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), (New Orleans, LA, USA), June 2022, pp. 2406-2415.
Details. Download: PDF.

[46]

ShapeMap 3-D: Efficient shape mapping through dense touch and vision
by S. Suresh, Z. Si, J. Mangelson, W. Yuan, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Philadelphia, PA, USA), May 2022, pp. 7073-7080.
Details. Download: PDF.

[47]

EDPLVO: Efficient Direct Point-Line Visual Odometry
by L. Zhou, G. Huang, Y. Mao, S. Wang, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Philadelphia, PA, USA), May 2022, pp. 7559-7565. Outstanding navigation paper award.
Details. Download: PDF.

[48]

PatchGraph: In-hand Tactile Tracking with Learned Surface Normals
by P. Sodhi, M. Kaess, M. Mukadam, and S. Anderson.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Philadelphia, PA, USA), May 2022, pp. 2164-2170.
Details. Download: PDF.

[49]

HoloOcean: An Underwater Robotics Simulator
by E. Potokar, S. Ashford, M. Kaess, and J. Mangelson.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Philadelphia, PA, USA), May 2022, pp. 3040-3046.
Details. Download: PDF.

[50]

Global Visual-Inertial Ground Vehicle State Estimation via Image Registration
by Y. Litman, D. McGann, E. Dexheimer, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Philadelphia, PA, USA), May 2022, pp. 8178-8184.
Details. Download: PDF.

[51]

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.

[52]

Map Compressibility Assessment for LiDAR Registration
by M.-F. Chang, W. Dong, J.G. Mangelson, M. Kaess, and S. Lucey.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Prague, Czech Republic), Sep. 2021, pp. 5560-5567.
Details. Download: PDF.

[53]

Ground Encoding: Learned Factor Graph-based Models for Localizing Ground Penetrating Radar
by A. Baikovitz, P. Sodhi, M. Dille, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Prague, Czech Republic), Sep. 2021, pp. 5476-5483. Best paper and best student paper finalist (one of five).
Details. Download: PDF.

[54]

Tactile SLAM: Real-time Inference of Shape and Pose from Planar Pushing
by S. Suresh, M. Bauza, K.-T. Yu, J.G. Mangelson, A. Rodriguez, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Xi'an, China), May 2021, pp. 11322-11328. Best service robotics paper finalist (one of four).
Details. Download: PDF.

[55]

Learning Tactile Models for Factor Graph-based Estimation
by P. Sodhi, M. Kaess, M. Mukadam, and S. Anderson.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Xi'an, China), May 2021, pp. 13686-13692.
Details. Download: PDF.

[56]

HyperMap: Compressed 3D Map for Monocular Camera Registration
by M.-F. Chang, J.G. Mangelson, M. Kaess, and S. Lucey.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Xi'an, China), May 2021, pp. 11739-11745.
Details. Download: PDF.

[57]

Compositional and Scalable Object SLAM
by A. Sharma, W. Dong, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Xi'an, China), May 2021, pp. 11626-11632.
Details. Download: PDF.

[58]

A Graph-Based Method for Joint Instance Segmentation of Point Clouds and Image Sequences
by M. Abello, J.G. Mangelson, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Xi'an, China), May 2021, pp. 9565-9571.
Details. Download: PDF.

[59]

π-LSAM: LiDAR Smoothing and Mapping With Planes
by L. Zhou, S. Wang, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Xi'an, China), May 2021, pp. 5751-5757.
Details. Download: PDF.

[60]

An Efficient Planar Bundle Adjustment Algorithm
by L. Zhou, D. Koppel, H. Ju, F. Steinbruecker, and M. Kaess.
In Proc. IEEE Intl. Symp. on Mixed and Augmented Reality, ISMAR, (Porto de Galinhas, Brazil), Nov. 2020, pp. 136-145.
Details. Download: PDF.

[61]

ARAS: Ambiguity-aware Robust Active SLAM based on Multi-hypothesis State and Map Estimations
by M. Hsiao, J.G. Mangelson, S. Suresh, C. Debrunner, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, Oct. 2020, pp. 5037-5044.
Details. Download: PDF.

[62]

Efficient Trajectory Library Filtering for Quadrotor Flight in Unknown Environments
by V.K. Viswanathan, E. Dexheimer, G. Li, G. Loianno, M. Kaess, and S. Scherer.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, Oct. 2020, pp. 2510-2517.
Details. Download: PDF.

[63]

Efficient Multiresolution Scrolling Grid for Stereo Vision-based MAV Obstacle Avoidance
by E. Dexheimer, J.G. Mangelson, S. Scherer, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, Oct. 2020, pp. 4758-4765.
Details. Download: PDF.

[64]

A Theory of Fermat Paths for 3D Imaging Sonar Reconstruction
by E. Westman, I. Gkioulekas, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, Oct. 2020, pp. 5082-5088.
Details. Download: PDF.

[65]

A Robust Multi-Stereo Visual-Inertial Odometry Pipeline
by J. Jaekel, J.G. Mangelson, S. Scherer, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, Oct. 2020, pp. 4623-4630.
Details. Download: PDF.

[66]

Characterizing Marginalization and Incremental Operations on the Bayes Tree
by D. Fourie, A.T. Espinoza, M. Kaess, and J.J. Leonard.
In Proc. Intl. Workshop on the Algorithmic Foundations of Robotics, WAFR, (Oulu, Finland), June 2020.
Details. Download: PDF.

[67]

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, May 2020, pp. 279-285.
Details. Download: PDF.

[68]

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, May 2020, pp. 3132-3138.
Details. Download: PDF.

[69]

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, May 2020.
Details. Download: PDF.

[70]

A Fast and Accurate Solution for Pose Estimation from 3D Correspondences
by L. Zhou, S. Wang, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, May 2020.
Details. Download: PDF.

[71]

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.

[72]

Wide Aperture Imaging Sonar Reconstruction using Generative Models
by E. Westman and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Macao), Nov. 2019, pp. 8067-8074.
Details. Download: PDF.

[73]

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.

[74]

Dense Sonar-based Reconstruction of Underwater Scenes
by P.V. Teixeira, D. Fourie, M. Kaess, and J.J. Leonard.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Macao), Nov. 2019, pp. 8060-8066.
Details. Download: PDF.

[75]

Degeneracy-Aware Factors with Applications to Underwater SLAM
by A. Hinduja, B. Ho, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Macao), Nov. 2019, pp. 1293-1299.
Details. Download: PDF.

[76]

An Efficient and Accurate Algorithm for the Perspective-n-Point Problem
by L. Zhou and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Macao), Nov. 2019, pp. 6245-6252.
Details. Download: PDF.

[77]

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.

[78]

Surfel-Based Dense RGB-D Reconstruction with Global and Local Consistency
by Y. Yang, W. Dong, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Montreal, Canada), May 2019, pp. 5238-5244.
Details. Download: PDF.

[79]

Multi-view Reconstruction of Wires using a Catenary Model
by R. Madaan, M. Kaess, and S. Scherer.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Montreal, Canada), May 2019, pp. 5657-5664.
Details. Download: PDF.

[80]

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.

[81]

A Robust and Efficient Algorithm for the PnL Problem Using Algebraic Distance to Approximate the Reprojection Distance
by L. Zhou, Y. Yang, M. Abello, and M. Kaess.
In Proc. AAAI Conference on Artificial Intelligence, AAAI, (Honolulu, Hawaii, USA), Jan. 2019, pp. 9307-9315.
Details. Download: PDF.

[82]

A Stable Algebraic Camera Pose Estimation for Minimal Configurations of 2D/3D Point and Line Correspondences
by L. Zhou, J. Ye, and M. Kaess.
In Proc. Asian Conf. on Computer Vision, ACCV, (Perth, Australia), Dec. 2018, pp. 273-288.
Details. Download: PDF.

[83]

Virtual Occupancy Grid Map for Submap-based Pose Graph SLAM and Planning in 3D Environments
by B. Ho, P. Sodhi, P. Teixeira, M. Hsiao, T. Kusnur, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Madrid, Spain), Oct. 2018, pp. 2175-2182.
Details. Download: PDF.

[84]

Multibeam Data Processing for Underwater Mapping
by P.V. Teixeira, M. Kaess, F.S. Hover, and J.J. Leonard.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Madrid, Spain), Oct. 2018, pp. 1877-1884.
Details. Download: PDF.

[85]

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, pp. 1146-1153. Best conference paper finalist (one of six).
Details. Download: PDF.

[86]

Automatic Extrinsic Calibration of a Camera and a 3D LiDAR using Line and Plane Correspondences
by L. Zhou, Z. Li, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Madrid, Spain), Oct. 2018, pp. 5562-5569.
Details. Download: PDF.

[87]

Feature-based SLAM for Imaging Sonar with Under-constrained Landmarks
by E. Westman, A. Hinduja, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Brisbane, Australia), May 2018, pp. 3629-3636.
Details. Download: PDF.

[88]

Dense Planar-Inertial SLAM with Structural Constraints
by M. Hsiao, E. Westman, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Brisbane, Australia), May 2018, pp. 6521-6528.
Details. Download: PDF.

[89]

GravityFusion: Real-time Dense mapping without Pose Graph using Deformation and Orientation
by P. Puri, D. Jia, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Vancouver, Canada), Sep. 2017, pp. 6506-6513.
Details. Download: PDF.

[90]

The Manifold Particle Filter for State Estimation on High-dimensional Implicit Manifolds
by M. C. Koval, M. Klingensmith, S. S. Srinivasa, N. S. Pollard, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Singapore), May 2017, pp. 4673-4680.
Details. Download: PDF.

[91]

Robust Stereo Matching with Surface Normal Prediction
by S. Zhang, W. Xie, G. Zhang, H. Bao, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Singapore), May 2017, pp. 2540-2547.
Details. Download: PDF.

[92]

Keyframe-based Dense Planar SLAM
by M. Hsiao, E. Westman, G. Zhang, and M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Singapore), May 2017, pp. 5110-5117.
Details. Download: PDF.

[93]

Underwater Inspection using Sonar-based Volumetric Submaps
by P.V. Teixeira, M. Kaess, F.S. Hover, and J.J. Leonard.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Daejeon, Korea), Oct. 2016, pp. 4288-4295.
Details. Download: PDF.

[94]

Pop-up SLAM: Semantic Monocular Plane SLAM for Low-texture Environments
by S. Yang, Y. Song, M. Kaess, and S. Scherer.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Daejeon, Korea), Oct. 2016, pp. 1222-1229.
Details. Download: PDF.

[95]

Long-range GPS-denied Aerial Inertial Navigation with LIDAR Localization
by G. Hemann, S. Singh, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Daejeon, Korea), Oct. 2016, pp. 1659-1666.
Details. Download: PDF.

[96]

Incremental Data Association for Acoustic Structure from Motion
by T.A. Huang and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Daejeon, Korea), Oct. 2016, pp. 1334-1341.
Details. Download: PDF.

[97]

A Nonparametric Belief Solution to the Bayes Tree
by D. Fourie, J.J. Leonard, and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Daejeon, Korea), Oct. 2016, pp. 2189-2196.
Details. Download: PDF.

[98]

On Degeneracy of Optimization-based State Estimation Problems
by J. Zhang, M. Kaess, and S. Singh.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Stockholm, Sweden), May 2016, pp. 809-816.
Details. Download: PDF.

[99]

Towards Acoustic Structure from Motion for Imaging Sonar
by T.A. Huang and M. Kaess.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Hamburg, Germany), Sep. 2015, pp. 758-765.
Details. Download: PDF.

[100]

Bridging Text Spotting and SLAM with Junction Features
by H.-C. Wang, C. Finn, L. Paull, M. Kaess, R. Rosenholtz, S. Teller, and J.J. Leonard.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Hamburg, Germany), Sep. 2015, pp. 3701-3708.
Details. Download: PDF.

[101]

Simultaneous Localization and Mapping with Infinite Planes
by M. Kaess.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Seattle, WA), May 2015, pp. 4605-4611.
Details. Download: PDF.

[102]

Building 3D Mosaics from an Autonomous Underwater Vehicle and 2D Imaging Sonar
by P. Ozog, G. Troni, M. Kaess, R.M. Eustice, and M. Johnson-Roberson.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Seattle, WA), May 2015, pp. 1137-1143.
Details. Download: PDF.

[103]

Real-time Depth Enhanced Monocular Odometry
by J. Zhang, M. Kaess, and S. Singh.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Chicago, IL), Sep. 2014, pp. 4973-4980.
Details. Download: PDF.

[104]

3D Mapping, Localisation and Object Retrieval using Low Cost Robotic Platforms: A Robotic Search Engine for the Real-World
by T. Whelan, M. Kaess, R. Finman, M.F. Fallon, H. Johannsson, J.J. Leonard, and J. McDonald.
In RSS Workshop on RGB-D: Advanced Reasoning with Depth Cameras, (Berkeley, CA), July 2014.
Details. Download: PDF.

[105]

Towards Consistent Visual-Inertial Navigation
by G. Huang, M. Kaess, and J.J. Leonard.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Hong Kong), June 2014, pp. 4926-4933.
Details. Download: PDF.

[106]

Efficient Incremental Map Segmentation in Dense RGB-D Maps
by R. Finman, T. Whelan, M. Kaess, and J.J. Leonard.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Hong Kong), June 2014, pp. 5488-5494.
Details. Download: PDF.

[107]

Mapping 3D Underwater Environments with Smoothed Submaps
by M. VanMiddlesworth, M. Kaess, F.S. Hover, and J.J. Leonard.
In Proc. Conf. on Field and Service Robotics, FSR, (Brisbane, Australia), Dec. 2013, pp. 17-30.
Details. Download: PDF.

[108]

Deformation-based Loop Closure for Large Scale Dense RGB-D SLAM
by T. Whelan, M. Kaess, J.J. Leonard, and J.B. McDonald.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Tokyo, Japan), Nov. 2013, pp. 548-555.
Details. Download: PDF.

[109]

Unscented iSAM: A Consistent Incremental Solution to Cooperative Localization and Target Tracking
by G. Huang, R. Truax, M. Kaess, and J.J. Leonard.
In Proc. European Conf. on Mobile Robots, ECMR, (Barcelona, Spain), Sep. 2013, pp. 248-254.
Details. Download: PDF.

[110]

Toward Lifelong Object Segmentation from Change Detection in Dense RGB-D Maps
by R.E. Finman, T. Whelan, M. Kaess, and J.J. Leonard.
In Proc. European Conf. on Mobile Robots, ECMR, (Barcelona, Spain), Sep. 2013, pp. 178-185.
Details. Download: PDF.

[111]

Consistent Sparsification for Graph Optimization
by G. Huang, M. Kaess, and J.J. Leonard.
In Proc. European Conf. on Mobile Robots, ECMR, (Barcelona, Spain), Sep. 2013, pp. 150-157.
Details. Download: PDF.

[112]

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, pp. 54-61. Best student paper finalist (one of five).
Details. Download: PDF.

[113]

Robust Real-Time Visual Odometry for Dense RGB-D Mapping
by T. Whelan, H. Johannsson, M. Kaess, J.J. Leonard, and J.B. McDonald.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Karlsruhe, Germany), May 2013, pp. 5724-5731.
Details. Download: PDF.

[114]

Robust Incremental Online Inference Over Sparse Factor Graphs: Beyond the Gaussian Case
by D.M. Rosen, M. Kaess, and J.J. Leonard.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Karlsruhe, Germany), May 2013, pp. 1025-1032.
Details. Download: PDF.

[115]

Analytically-Selected Multi-Hypothesis Incremental Map Estimation
by G. Huang, M. Kaess, J.J. Leonard, and S.I. Roumeliotis.
In Proc. Intl. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, (Vancouver, Canada), May 2013.
Details. Download: PDF.

[116]

Dynamic Pose Graph SLAM: Long-term Mapping in Low Dynamic Environments
by A. Walcott-Bryant, M. Kaess, H. Johannsson, and J.J. Leonard.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Vilamoura, Portugal), Oct. 2012, pp. 1871-1878.
Details. Download: PDF.

[117]

Temporally Scalable Visual SLAM using a Reduced Pose Graph
by H. Johannsson, M. Kaess, M.F. Fallon, and J.J. Leonard.
In RSS Workshop on Long-term Operation of Autonomous Robotic Systems in Changing Environments, (Sydney, Australia), July 2012.
Details. Download: PDF.

[118]

Kintinuous: Spatially Extended KinectFusion
by T. Whelan, J.B. McDonald, M. Kaess, M.F. Fallon, H. Johannsson, and J.J. Leonard.
In RSS Workshop on RGB-D: Advanced Reasoning with Depth Cameras, (Sydney, Australia), July 2012.
Details. Download: PDF.

[119]

Factor Graph Based Incremental Smoothing in Inertial Navigation Systems
by V. Indelman, S. Williams, M. Kaess, and F. Dellaert.
In Proc. Intl. Conf. on Information Fusion, FUSION, (Singapore), July 2012, pp. 2154-2161.
Details. Download: PDF.

[120]

Concurrent Filtering and Smoothing
by M. Kaess, S. Williams, V. Indelman, R. Roberts, J.J. Leonard, and F. Dellaert.
In Proc. Intl. Conf. on Information Fusion, FUSION, (Singapore), July 2012, pp. 1300-1307.
Details. Download: PDF.

[121]

An Incremental Trust-Region Method for Robust Online Sparse Least-Squares Estimation
by D.M. Rosen, M. Kaess, and J.J. Leonard.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (St. Paul, MN), May 2012, pp. 1262-1269.
Details. Download: PDF.

[122]

6-DOF Multi-session Visual SLAM using Anchor Nodes
by J.B. McDonald, M. Kaess, C. Cadena, J. Neira, and J.J. Leonard.
In European Conference on Mobile Robots, ECMR, (Orebro, Sweden), Sep. 2011, pp. 69-76.
Details. Download: PDF.

[123]

iSAM2: Incremental Smoothing and Mapping with Fluid Relinearization and Incremental Variable Reordering
by M. Kaess, H. Johannsson, R. Roberts, V. Ila, J.J. Leonard, and F. Dellaert.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Shanghai, China), May 2011, pp. 3281-3288.
Details. Download: PDF.

[124]

Efficient AUV Navigation Fusing Acoustic Ranging and Side-scan Sonar
by M.F. Fallon, M. Kaess, H. Johannsson, and J.J. Leonard.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Shanghai, China), May 2011, pp. 2398-2405. Best automation paper finalist (one of five).
Details. Download: PDF.

[125]

The Bayes Tree: An Algorithmic Foundation for Probabilistic Robot Mapping
by M. Kaess, V. Ila, R. Roberts, and F. Dellaert.
In Proc. Intl. Workshop on the Algorithmic Foundations of Robotics, WAFR, (Singapore), Dec. 2010, pp. 157-173.
Details. Download: PDF.

[126]

Imaging Sonar-Aided Navigation for Autonomous Underwater Harbor Surveillance
by H. Johannsson, M. Kaess, B.J. Englot, F.S. Hover, and J.J. Leonard.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (Taipei, Taiwan), Oct. 2010, pp. 4396-4403.
Details. Download: PDF.

[127]

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.

[128]

Flow Separation for Fast and Robust Stereo Odometry
by M. Kaess, K. Ni, and F. Dellaert.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Kobe, Japan), May 2009, pp. 3539-3544.
Details. Download: PDF.

[129]

Place Recognition-based Fixed-Lag Smoothing for Environments with Unreliable GPS
by R. Mottaghi, M. Kaess, A. Ranganathan, R. Roberts, and F. Dellaert.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Pasadena, CA), May 2008, pp. 1862-1867.
Details. Download: PDF.

[130]

Fast 3D Pose Estimation With Out-of-Sequence Measurements
by A. Ranganathan, M. Kaess, and F. Dellaert.
In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, (San Diego, CA), Oct. 2007, pp. 2486-2493.
Details. Download: PDF.

[131]

iSAM: Fast Incremental Smoothing and Mapping with Efficient Data Association
by M. Kaess, A. Ranganathan, and F. Dellaert.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Rome, Italy), Apr. 2007, pp. 1670-1677.
Details. Download: PDF.

[132]

Loopy SAM
by A. Ranganathan, M. Kaess, and F. Dellaert.
In Proc. Intl. Joint Conf. on Artificial Intelligence, IJCAI, (Hyderabad, India), Jan. 2007, pp. 2191-2196. Oral presentation acceptance ratio 15.7% (212 of 1353).
Details. Download: PDF.

[133]

Fast Incremental Square Root Information Smoothing
by M. Kaess, A. Ranganathan, and F. Dellaert.
In Proc. Intl. Joint Conf. on Artificial Intelligence, IJCAI, (Hyderabad, India), Jan. 2007, pp. 2129-2134. Oral presentation acceptance ratio 15.7% (212 of 1353).
Details. Download: PDF.

[134]

A Markov Chain Monte Carlo Approach to Closing the Loop in SLAM
by M. Kaess and F. Dellaert.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Barcelona, Spain), Apr. 2005, pp. 645-650.
Details. Download: PDF.

[135]

MCMC-based Multiview Reconstruction of Piecewise Smooth Subdivision Curves with a Variable Number of Control Points
by M. Kaess, R. Zboinski, and F. Dellaert.
In Proc. European Conf. on Computer Vision, ECCV, (Prague, Czech Republic), May 2004, pp. 329-341. Acceptance ratio 34.2% (190 of 555).
Details. Download: PDF.

[136]

Reconstruction of Objects with Jagged Edges through Rao-Blackwellized Fitting of Piecewise Smooth Subdivision Curves
by M. Kaess and F. Dellaert.
In Proceedings of the IEEE 1st International Workshop on Higher-Level Knowledge in 3D Modeling and Motion Analysis, (Nice, France), Oct. 2003, pp. 39-47.
Details. Download: PDF.

[137]

Compact Encoding of Robot-Generated 3D Maps for Efficient Wireless Transmission
by M. Kaess, R.C. Arkin, and J. Rossignac.
In Proc. IEEE Intl. Conf. on Advanced Robotics, ICAR, (Coimbra, Portugal), June 2003, pp. 324-331.
Details. Download: PDF.

[138]

Learning Behavioral Parameterization Using Spatio-Temporal Case-Based Reasoning
by M. Likhachev, M. Kaess, and R.C. Arkin.
In Proc. IEEE Intl. Conf. on Robotics and Automation, ICRA, (Washington, DC), May 2002, pp. 1282-1289.
Details. Download: PDF.

Other publications

[139]

Underwater AprilTag SLAM and Calibration for High Precision Robot Localization
by E. Westman and M. Kaess, Robotics Institute.
Carnegie Mellon University technical report CMU-RI-TR-18-43, Oct. 2018.
Details. Download: PDF.

[140]

Localized Imaging and Mapping for Underwater Fuel Storage Basins
by J. Hsiung, A. Tallaksen, L. Papincak, S. Suresh, H. Jones, W. Whittaker, and M. Kaess.
In Proc. of the Symposium on Waste Management, (Phoenix, Arizona), Mar. 2018.
Details.

[141]

Robust Keyframe-based Dense SLAM with an RGB-D Camera
by H. Liu, C. Li, G. Chen, G. Zhang, M. Kaess, and H. Bao.
ArXiv technical report arXiv:1711.05166, Nov. 2017.
Details. Download: PDF.

[142]

Perception for Safe Autonomous Helicopter Flight and Landing
by S. Singh, H. Cover, A. Stambler, B. Grocholsky, J. Mishler, B. Hamner, K. Strabala, G. Sherwin, M. Kaess, G. Hemann, M. Bergerman, and S. Spiker.
In 72nd Annual Forum and Technology Display, American Helicopter Society (AHS), May 2016.
Details.

[143]

The Manifold Particle Filter for State Estimation on High-dimensional Implicit Manifolds
by M. Klingensmith, M.C. Koval, S.S. Srinivasa, N.S. Pollard, and M. Kaess.
ArXiv technical report arXiv:1604.07224, Apr. 2016.
Details. Download: PDF.

[144]

Robust Tracking for Real-Time Dense RGB-D Mapping with Kintinuous
by T. Whelan, H. Johannsson, M. Kaess, J.J. Leonard, and J.B. McDonald, Computer Science and Artificial Intelligence Laboratory.
MIT technical report MIT-CSAIL-TR-2012-031, Sep. 2012.
Details. Download: PDF.

[145]

Mapping the MIT Stata Center: Large-Scale Integrated Visual and RGB-D SLAM
by M.F. Fallon, H. Johannsson, M. Kaess, D.M. Rosen, E. Muggler, and J.J. Leonard.
In RSS Workshop on RGB-D: Advanced Reasoning with Depth Cameras, July 2012.
Details. Download: PDF.

[146]

Towards Autonomous Ship Hull Inspection using the Bluefin HAUV
by M. Kaess, H. Johannsson, B. Englot, F.S. Hover, and J.J. Leonard.
In Ninth Intl. Symposium on Technology and the Mine Problem, (Naval Postgraduate School, Monterey, CA), May 2010.
Details. Download: PDF.

[147]

The Bayes Tree: Enabling Incremental Reordering and Fluid Relinearization for Online Mapping
by M. Kaess, V. Ila, R. Roberts, and F. Dellaert, Computer Science and Artificial Intelligence Laboratory.
MIT technical report MIT-CSAIL-TR-2010-021, Jan. 2010.
Details. Download: PDF.

[148]

Evaluating the Performance of Robot Mapping Systems
by E. Olson and M. Kaess.
In Workshop on Good Experimental Methodology in Robotics, 2009.
Details. Download: PDF.

[149]

Visual SLAM with a Multi-Camera Rig
by M. Kaess and F. Dellaert.
Georgia Institute of Technology technical report GIT-GVU-06-06, Feb. 2006.
Details. Download: PDF.

[150]

The Georgia Tech Yellow Jackets: A Marsupial Team for Urban Search and Rescue
by F. Dellaert, T. Balch, M. Kaess, R. Ravichandran, F. Alegre, M. Berhault, R. McGuire, E. Merrill, L. Moshkina, and D. Walker.
In AAAI Mobile Robot Competition, (Edmonton, Alberta, Canada), 2002, pp. 44-49.
Details. Download: PDF.

Last updated: March 21, 2023