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A solution to the simultaneous localization and map building (SLAM) problem
Abstract
The simultaneous localization and map building (SLAM) problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to incrementally build a map of this environment while simultaneously using this map to compute absolute vehicle location. Starting from estimation-theoretic foundations of this problem, the paper proves that a solution to the SLAM problem is indeed possible. The underlying structure of the SLAM problem is first elucidated. A proof that the estimated map converges monotonically to a relative map with zero uncertainty is then developed. It is then shown that the absolute accuracy of the map and the vehicle location reach a lower bound defined only by the initial vehicle uncertainty. Together, these results show that it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and, using relative observations only, incrementally build a perfect map of the world and to compute simultaneously a bounded estimate of vehicle location. The paper also describes a substantial implementation of the SLAM algorithm on a vehicle operating in an outdoor environment using millimeter-wave radar to provide relative map observations. This implementation is used to demonstrate how some key issues such as map management and data association can be handled in a practical environment. The results obtained are cross-compared with absolute locations of the map landmarks obtained by surveying. In conclusion, the paper discusses a number of key issues raised by the solution to the SLAM problem including suboptimal map-building algorithms and map management.
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“In light of this drawback Montemerlo et al. [195] introduced FastSLAM, an algorithm that recursively approximates the entire posterior distribution over robot pose and landmark locations, yet scales exponentially with the number of landmarks on the map.”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as Montemerlo et al. [195]
In the citing paper
“FastSLAM uses a hybrid technique that integrates Particle Filter and EKF approach, making it popular for its higher data accuracy [193, 195].”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [195]
Citations
Cites
A robust layered control system for a mobile robot
Brooks, R. (1986) · IEEE Journal on Robotics and Automation · doi:10.1109/jra.1986.1087032 · Cited by 7,799
Stochastic models, estimation, and control
(1982) · Mathematics in Science and Engineering/Mathematics in science and engineering · doi:10.1016/s0076-5392(08)x6186-7 · Cited by 3,230
Bar‐Shalom, Y. (1988) · Medical Entomology and Zoology · Cited by 3,157
Bar‐Shalom, Y., Fortmann, T. E., & Cable, P. G. (1990) · The Journal of the Acoustical Society of America · doi:10.1121/1.398863 · Cited by 3,088
Iterative point matching for registration of free-form curves and surfaces
Zhang, Z. (1994) · International Journal of Computer Vision · doi:10.1007/bf01427149 · Cited by 2,438
On the Representation and Estimation of Spatial Uncertainty
Smith, R. C., & Cheeseman, P. C. (1986) · The International Journal of Robotics Research · doi:10.1177/027836498600500404 · Cited by 1,624
Estimating Uncertain Spatial Relationships in Robotics
Smith, R. K., Self, M., & Cheeseman, P. (1990) · Springer eBooks · doi:10.1007/978-1-4613-8997-2_14 · Cited by 1,289
Directed Sonar Sensing for Mobile Robot Navigation
Leonard, J. J., & Durrant-Whyte, H. F. (1992) · Springer eBooks · doi:10.1007/978-1-4615-3652-9 · Cited by 798
Self-citationA Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots
Thrun, S., Burgard, W., & Fox, D. (1998) · Machine Learning · doi:10.1023/a:1007436523611 · Cited by 795
Estimating uncertain spatial relationships in robotics
Smith, R., Self, M., & Cheeseman, P. (2005) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.1987.1087846 · Cited by 761
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Chatterjee, A., & Matsuno, F. (2007) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2007.894972 · Cited by 88
Scan Alignment and 3-D Surface Modeling with a Helicopter Platform
Thrun, S., Diel, M., & Hähnel, D. (2006) · Springer tracts in advanced robotics · doi:10.1007/10991459_28 · Cited by 88
Equiangular navigation and guidance of a wheeled mobile robot based on range-only measurements
Teimoori, H., & Savkin, A. V. (2009) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2009.09.004 · Cited by 86
Towards Constant-Time SLAM on an Autonomous Underwater Vehicle Using Synthetic Aperture Sonar
Newman, P. M., Leonard, J. J., & Rikoski, R. J. (2005) · Springer tracts in advanced robotics · doi:10.1007/11008941_44 · Cited by 86
Self-citationA review of visual inertial odometry from filtering and optimisation perspectives
Gui, J.-J., Gu, D.-B., Wang, S., & Hu, H.-S. (2015) · Adv. Robotics · doi:10.1080/01691864.2015.1057616 · Cited by 95
Large-scale mapping in complex field scenarios using an autonomous car
Mutz, F. W., Veronese, L. D. P., Oliveira-Santos, T., de Aguiar, E., Cheein, F. A., & Souza, A. F. D. (2015) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.10.045 · Cited by 86
Anchor self-localization algorithm based on UWB ranging and inertial measurements
Shi, Q., Zhao, S., Cui, X., Lu, M., & Jia, M. (2019) · Tsinghua Science & Technology · doi:10.26599/tst.2018.9010102 · Cited by 85
Aslan, M. F., Durdu, A., & Sabancı, K. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.110156 · Cited by 88
The fusion of large scale classified side-scan sonar image mosaics
Reed, S., Ruiz, I. T., Capus, C., & Pétillot, Y. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.873448 · Cited by 85
On mobile robot localization from landmark bearings
Shimshoni, I. (2002) · IEEE Transactions on Robotics and Automation · doi:10.1109/tra.2002.805663 · Cited by 85
An efficient multiple hypothesis filter for bearing-only SLAM
Kwok, N. M., & Dissanayake, G. (2005) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2004.1389440 · Cited by 84
Distributed Multi-Robot Exploration and Mapping
Fox, D. (2005) · Canadian Conference on Computer and Robot Vision · doi:10.1109/crv.2005.36 · Cited by 86
Mapping Partially Observable Features from Multiple Uncertain Vantage Points
Leonard, J. J., Rikoski, R. J., Newman, P. M., & Bosse, M. C. (2002) · The International Journal of Robotics Research · doi:10.1177/0278364902021010889 · Cited by 84
Self-citationRobust rigid registration algorithm based on pointwise correspondence and correntropy
Du, S., Xu, G., Zhang, S., Zhang, X., Gao, Y., & Chen, B. (2018) · Pattern Recognition Letters · doi:10.1016/j.patrec.2018.06.028 · Cited by 83
Simultaneous Localization and Mapping in the Epoch of Semantics: A Survey
Sualeh, M., & Kim, G.-W. (2018) · International Journal of Control Automation and Systems · doi:10.1007/s12555-018-0130-x · Cited by 85
SLAM-aided forest plot mapping combining terrestrial and mobile laser scanning
Shao, J., Zhang, W., Mellado, N., Wang, N., Jin, S., Cai, S., Luo, L., Lejemble, T., & Yan, G. (2020) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2020.03.008 · Cited by 83
Thrun, S., Montemerlo, M., Koller, D., Wegbreit, B., Nieto, J. I., & Nebot, E. (2004) · Cited by 81
Sensor-based robot motion generation in unknown, dynamic and troublesome scenarios
Mínguez, J., & Montano, L. (2005) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2005.06.001 · Cited by 81
Marco, M. D., Garulli, A., Giannitrapani, A., & Vicino, A. (2003) · IEEE Transactions on Robotics and Automation · doi:10.1109/tra.2003.808849 · Cited by 81
Bioinspired Intelligent Algorithm and Its Applications for Mobile Robot Control: A Survey
Ni, J., Wu, L., Fan, X., & Yang, S. X. (2016) · Computational Intelligence and Neuroscience · doi:10.1155/2016/3810903 · Cited by 92
Representation granularity enables time-efficient autonomous exploration in large, complex worlds
Cao, C., Zhu, H., Ren, Z., Choset, H., & Zhang, J. (2023) · Science Robotics · doi:10.1126/scirobotics.adf0970 · Cited by 79
Large-area visually augmented navigation for autonomous underwater vehicles
Eustice, R. M. (2005) · doi:10.1575/1912/1414 · Cited by 78
Discrete-Status-Based Localization for Indoor Service Robots
Lee, D., & Chung, W. (2006) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2006.881949 · Cited by 78
Intelligent Reflecting Surface Enhanced Indoor Robot Path Planning: A Radio Map-Based Approach
Mu, X., Liu, Y., Guo, L., Lin, J., & Schober, R. (2021) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2021.3062089 · Cited by 77
SLAM Overview: From Single Sensor to Heterogeneous Fusion
Chen, W., Zhou, C., Shang, G., Wang, X., Li, Z., Xu, C., & Hu, K. (2022) · Remote Sensing · doi:10.3390/rs14236033 · Cited by 88
Kelly, A., Nagy, B., Stager, D., & Unnikrishnan, R. (2007) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2007.901317 · Cited by 77
Orthogonal SLAM: a Step toward Lightweight Indoor Autonomous Navigation
Nguyen, V., Harati, A., Martinelli, A., Siegwart, R., & Tomatis, N. (2006) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2006.282527 · Cited by 77
Novel Technique for Vision-Based UAV Navigation
Zhang, J., Liu, W., & Wu, Y. (2011) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2011.6034661 · Cited by 77
Map Management for Efficient Simultaneous Localization and Mapping (SLAM)
Dissanayake, G., Williams, S. B., Durrant-Whyte, H. F., & Bailey, T. (2002) · Autonomous Robots · doi:10.1023/a:1015217631658 · Cited by 77
Self-citationPlanning under uncertainty using model predictive control for information gathering
Leung, C., Huang, S., Kwok, N., & Dissanayake, G. (2006) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2006.05.008 · Cited by 76
RF Localization for Wireless Video Capsule Endoscopy
Pahlavan, K., Bao, G., Ye, Y., Makarov, S. N., Khan, U., Swar, P., Cave, D. R., Karellas, A., Krishnamurthy, P., & Sayrafian, K. (2012) · International Journal of Wireless Information Networks · doi:10.1007/s10776-012-0195-z · Cited by 76
Extended Kalman filter-based mobile robot localization with intermittent measurements
Ahmad, H., & Namerikawa, T. (2013) · Systems Science & Control Engineering · doi:10.1080/21642583.2013.864249 · Cited by 76
P-SLAM: Simultaneous Localization and Mapping With Environmental-Structure Prediction
Chang, H.-Y., Lee, C. S. G., Lu, Y.-H., & Hu, Y. (2007) · IEEE Transactions on Robotics · doi:10.1109/tro.2007.892230 · Cited by 76
Occupancy grid mapping: An empirical evaluation
Collins, T., Collins, J. J., & Ryan, C. (2007) · Mediterranean Conference on Control and Automation (MED) · doi:10.1109/med.2007.4433772 · Cited by 74
High Fidelity Tools for Rescue Robotics: Results and Perspectives
Carpin, S., Wang, J., Lewis, M., Birk, A., & Jacoff, A. S. (2006) · Lecture notes in computer science · doi:10.1007/11780519_27 · Cited by 74
Gaussian Process Assisted Fingerprinting Localization
Yiu, S., & Yang, K. (2015) · IEEE Internet of Things Journal · doi:10.1109/jiot.2015.2481932 · Cited by 73
SLAM Gets a PHD: New Concepts in Map Estimation
Adams, M. D., Vo, B., Mahler, R., & Mullane, J. S. (2014) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2014.2304111 · Cited by 72
RadarSLAM: A robust simultaneous localization and mapping system for all weather conditions
Hong, Z., Pétillot, Y., Wallace, A. M., & Wang, S. (2022) · The International Journal of Robotics Research · doi:10.1177/02783649221080483 · Cited by 92
Are We Ready for Radar to Replace Lidar in All-Weather Mapping and Localization?
Burnett, K., Wu, Y., Yoon, D. J., Schoellig, A. P., & Barfoot, T. D. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3192885 · Cited by 72
Robust Real-Time Visual SLAM Using Scale Prediction and Exemplar Based Feature Description
Chekhlov, D., Pupilli, M., Mayol-Cuevas, W. W., & Calway, A. D. (2007) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2007.383026 · Cited by 73
Simple yet stable bearing‐only navigation
Krajník, T., Faigl, J., Vonásek, V., Košnar, K., Kulich, M., & Přeučil, L. (2010) · Journal of Field Robotics · doi:10.1002/rob.20354 · Cited by 72
Winfield, A. F. T. (2009) · Springer eBooks · doi:10.1007/978-0-387-30440-3_217 · Cited by 73
Dames, P., & Kumar, V. (2015) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2015.2425212 · Cited by 71
Network Navigation With Scheduling: Error Evolution
Wang, T., Shen, Y., Conti, A., & Win, M. Z. (2017) · IEEE Transactions on Information Theory · doi:10.1109/tit.2017.2717582 · Cited by 71
On the Mahalanobis Distance Classification Criterion for Multidimensional Normal Distributions
Gallego, G., Cuevas, C., Mohedano, R., & Garcia, N. N. (2013) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2013.2269047 · Cited by 71
Bearing-only SLAM Using a SPRT Based Gaussian Sum Filter
Kwok, N. M., Dissanayake, G., & Ha, Q. P. (2006) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2005.1570264 · Cited by 71
GPS/DR Error Estimation for Autonomous Vehicle Localization
Lee, B.-H., Song, J., Im, J.-H., Im, S.-H., Heo, M.-B., & Jee, G.-I. (2015) · Sensors · doi:10.3390/s150820779 · Cited by 71
Begum, M., Mann, G. K. I., & Gosine, R. G. (2006) · Applied Soft Computing · doi:10.1016/j.asoc.2006.11.010 · Cited by 71
A pure probabilistic approach to range-only SLAM
Blanco, J., Gonzalez, J., & Fernández‐Madrigal, J. (2008) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2008.4543404 · Cited by 70
A critique of current developments in simultaneous localization and mapping
Huang, S., & Dissanayake, G. (2016) · International Journal of Advanced Robotic Systems · doi:10.1177/1729881416669482 · Cited by 71
AUV Benthic Habitat Mapping in South Eastern Tasmania
Williams, S. B., Pizarro, O. R., Jakuba, M. V., & Barrett, N. S. (2010) · Springer tracts in advanced robotics · doi:10.1007/978-3-642-13408-1_25 · Cited by 70
Radio SLAM: A Review on Radio-Based Simultaneous Localization and Mapping
Amjad, B., Ahmed, Q. Z., Lazaridis, P. I., Hafeez, M., Khan, F. A., & Zaharis, Z. D. (2023) · IEEE Access · doi:10.1109/access.2023.3237330 · Cited by 73
Cubature information filter and its applications
Chandra, K. P. B., Chandra, B., Gu, D., & Postlethwaite, I. (2011) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2011.5990913 · Cited by 69
A Novel Measure of Uncertainty for Mobile Robot SLAM with Rao—Blackwellized Particle Filters
Blanco, J., Fernández‐Madrigal, J., & González, J. (2007) · The International Journal of Robotics Research · doi:10.1177/0278364907082610 · Cited by 67
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Capuano, V., Kim, K., Harvard, A., & Chung, S. (2019) · Acta Astronautica · doi:10.1016/j.actaastro.2019.09.027 · Cited by 68
Wyeth, G. F., & Milford, M. J. (2009) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2009.933620 · Cited by 72
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Kim, J., & Sukkarieh, S. (2005) · Journal of Global Positioning Systems · doi:10.5081/jgps.4.1.120 · Cited by 68
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García, M., & Solanas, A. (2004) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2004.1307255 · Cited by 68
Williams, S. B., Pizarro, O. R., Webster, J. M., Beaman, R. J., Mahon, I., Johnson‐Roberson, M., & Bridge, T. C. L. (2010) · Journal of Field Robotics · doi:10.1002/rob.20356 · Cited by 69
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Probabilistic Type Theory and Natural Language Semantics
Cooper, R., Dobnik, S., Lappin, S., & Larsson, S. (2015) · Linguistic Issues in Language Technology · doi:10.33011/lilt.v10i.1357 · Cited by 64
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Hesch, J. A., Mirzaei, F. M., Mariottini, G. L., & Roumeliotis, S. I. (2010) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2010.5509693 · Cited by 65
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Nashashibi, F., & Bargeton, A. (2008) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2008.4621244 · Cited by 65
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Tuna, G., Mumcu, T. V., Gülez, K., Güngör, V. Ç., & Erturk, H. (2012) · Communications in computer and information science · doi:10.1007/978-3-642-31837-5_44 · Cited by 65
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Castro, M. D., Ferré, M., & Masi, A. (2018) · IEEE Access · doi:10.1109/access.2018.2849572 · Cited by 64
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Nieto, J. I., Bailey, T., & Nebot, E. (2006) · Springer eBooks · doi:10.1007/978-3-540-33453-8_15 · Cited by 64
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Naseri, H., & Koivunen, V. (2016) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2016.2616324 · Cited by 63
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Törnqvist, D. (2008) · Cited by 62
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Zhao, M., Lu, H., Yang, S., & Guo, F. (2020) · IEEE Access · doi:10.1109/access.2020.2978077 · Cited by 62
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Autonomous Driving: Context and State-of-the-Art
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Lisien, B., Morales, D., Silver, D., Kantor, G. A., Rekleitis, I. M., & Choset, H. (2005) · IEEE Transactions on Robotics · doi:10.1109/tro.2004.837237 · Cited by 61
Duro, R. J., Graña, M., & de Lope, J. (2010) · Information Sciences · doi:10.1016/j.ins.2010.02.005 · Cited by 62
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Maffei, G., Santos-Pata, D., Marcos, E., Sánchez-Fibla, M., & Verschure, P. F. M. J. (2015) · Neural Networks · doi:10.1016/j.neunet.2015.10.004 · Cited by 60
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Gouveia, B., Portugal, D., Silva, D. C., & Marques, L. (2014) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2014.2357216 · Cited by 60
Yuan, X., Martínez-Ortega, J.-F., Eckert, M., & López, L. (2016) · Sensors · doi:10.3390/s16071148 · Cited by 60
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Zhang, J., Wu, Y., Liu, W., & Chen, X. (2010) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2010.5461649 · Cited by 59
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An, S., Zhu, H., Wei, D., Tsintotas, K. A., & Gasteratos, A. C. (2022) · Journal of Field Robotics · doi:10.1002/rob.22060 · Cited by 58
Chen, X., Purohit, A., Ruiz, C., Carpin, S., & Zhang, P. (2015) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/2809695.2809724 · Cited by 57
Subjective local maps for hybrid metric-topological SLAM
Blanco, J., González, J., & Fernández‐Madrigal, J. (2008) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2008.02.002 · Cited by 58
Mapping and Pursuit-Evasion Strategies For a Simple Wall-Following Robot
Katsev, M., Yershova, A., Tovar, B., Ghrist, R., & LaValle, S. M. (2011) · IEEE Transactions on Robotics · doi:10.1109/tro.2010.2095570 · Cited by 57
Metadata
- Authors
- Dissanayake, M. W. M. G., Newman, P., Clark, S., Durrant-Whyte, H. F., & Csorba, M.
- Affiliations
- The University of Sydney (AU)
- ORCID
- Venue
- IEEE Transactions on Robotics and Automation
- Published
- 2001-06
- Volume
- 17
- Issue
- 3
- Pages
- 229-241
- ISSN
- 1042-296X (ISSN-L)
- OpenAlex
- W2143864104
- Cited by
- 2,661
- References
- 29
- Citations by year
- 2026: 37 · 2025: 48 · 2024: 52 · 2023: 63 · 2022: 83 · 2021: 88 · 2020: 109 · 2019: 109 · 2018: 120 · 2017: 108 · 2016: 116 · 2015: 115 · 2014: 137 · 2013: 119 · 2012: 140
- FWCI
- 158.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Robotics and Automation (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
- Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Indoor and Outdoor Localization Technologies
- Keywords
- SLAM, autonomous vehicles, map building, vehicle localization, estimation theory, lower bounds, millimeter-wave radar, data association, map management
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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