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A Spectral Learning Approach to Range-Only SLAM
[article]
2012
arXiv
pre-print
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We present a novel spectral learning algorithm for simultaneous localization and mapping (SLAM) from range data with known correspondences. ...
can cause severe errors in EKFs and EIFs, and to a lesser extent MHT, particularly for the highly non-Gaussian posteriors encountered in range-only SLAM. ...
Finally, we demonstrate that our spectral approach to SLAM beats other state-of-the-art SLAM approaches on real-world range-only SLAM problems. ...
arXiv:1207.2491v1
fatcat:747jknsjrbf3hhxxgqsoewiwzy
A Spectral Learning Approach to Range-Only SLAM
2018
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We present a novel spectral learning algorithm for simultaneous localization and mapping (SLAM) from range data with known correspondences. ...
Compared with popular batch optimization or multiple-hypothesis tracking (MHT) methods for range-only SLAM, our spectral approach o↵ers guaranteed low computational requirements and good tracking performance ...
Inspired by SfM, we reformulate range-only SLAM problem in a similar way in Section 3, and then similarly solve the problem with a spectral learning algorithm. ...
doi:10.1184/r1/6475436
fatcat:pkci57j7onawhckqcmt6s24kmu
The Early-type Stars from LAMOST survey: Atmospheric parameters
[article]
2021
arXiv
pre-print
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We apply two consistency tests to verify this machine learning method and compare stellar labels given by SLAM with that in literature for several objects having high-resolution spectra. ...
Here we report our work on adopting the data-driven technique Stellar LAbel Machine (SLAM) with the non-LTE TLUSTY synthetic spectra as the training dataset to estimate the stellar parameters of LAMOST ...
Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope LAMOST) is a National Major Scientific Project built by the Chinese ...
arXiv:2110.06246v1
fatcat:evcx3yyvhva2nf5msuui2b3al4
Affinity and Penalty Jointly Constrained Spectral Clustering With All-Compatibility, Flexibility, and Robustness
2017
IEEE Transactions on Neural Networks and Learning Systems
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Finally, both TI-APJCSC and TII-APJCSC demonstrate strong robustness, not only to the number of pairwise constraints but also to the parameter for affinity measurement. ...
The existing, semisupervised, spectral clustering approaches have two major drawbacks, i.e., either they cannot cope with multiple categories of supervision or they sometimes exhibit unstable effectiveness ...
Acknowledgment The authors would like to thank B. Hami from MA, USA, for the editorial assistance in the preparation of this paper. ...
doi:10.1109/tnnls.2015.2511179
pmid:26915134
pmcid:PMC4990515
fatcat:kcdils5wczfmvffegccqllv34e
Deriving the stellar labels of LAMOST spectra with Stellar LAbel Machine (SLAM)
[article]
2019
arXiv
pre-print
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Thanks to the capability to model highly non-linear problems with SVR, SLAM generally can derive stellar labels over a wide range of spectral types. ...
To illustrate this capability, we test the performance of SLAM on stars ranging from Teff∼4000 to ∼8000 K trained on LAMOST spectra and stellar labels. ...
Taking advantages of the non-parametric nature of SVR, SLAM is able to fit multi-dimensional and highly non-linear relationship between the fluxes and stellar labels, which is very different from The Cannon ...
arXiv:1908.08677v2
fatcat:cvppcmg6xbg2lb7eipmahallhm
Neural RF SLAM for unsupervised positioning and mapping with channel state information
[article]
2022
arXiv
pre-print
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We present a neural network architecture for jointly learning user locations and environment mapping up to isometry, in an unsupervised way, from channel state information (CSI) values with no location ...
The neural network task is set prediction and is accordingly trained end-to-end. The proposed model learns an interpretable latent, i.e., user location, by just enforcing a physics-based decoder. ...
Spectral system identification is used to learn dynamical system parameters such as a state space, motion model, and observation model directly. ...
arXiv:2203.08264v1
fatcat:zrs3ofa7v5c3tehgzo5vf6jwcy
PHROG: A Multimodal Feature for Place Recognition
2017
Sensors
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Author Contributions: F.B. conceived, designed and developed the proposed method and its experimental validation; All other authors contributed their expertise to validate the proposal, evaluate and question ...
spectral ranges. ...
Knowing what happens globally to textures across different spectral ranges, we have decided to validate the detection step itself in order to choose the best detection approach, namely corner detection ...
doi:10.3390/s17051167
pmid:28531101
pmcid:PMC5470912
fatcat:qqw26dbt6vcoxl2ttrbx7uybiq
Exploring the stellar rotation of early-type stars in the LAMOST Medium-Resolution Survey. I. Catalog
[article]
2021
arXiv
pre-print
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We employed the Stellar LAbel Machine (SLAM) to derive their spectroscopic stellar parameters, drawing on Kurucz spectral synthesis models with 6000 K < T_eff < 15,000 K and -1 dex < [M/H] < 1 dex. ...
Although this is an intrinsic caveat that comes from the MRS's narrow wavelength coverage, it only has a minor effect on estimates of the stellar rotation rates because of the decent spectral resolution ...
The Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope; LAMOST) is a National Major Scientific Project built by the Chinese Academy of Sciences. ...
arXiv:2108.01212v2
fatcat:kkds2kcj7ngihgif7mmhu3g46a
Lifelong Map Learning for Graph-based SLAM in Static Environments
2010
Künstliche Intelligenz
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We present a novel approach to prune the pose graph so that it only grows when the robot acquires relevant new information about the environment in terms of expected information gain. ...
As a result, our approach scales with the size of the environment and not with the length of the trajectory, which is an important prerequisite for lifelong map learning. ...
Acknowledgements We would like to thank Dirk Hähnel for providing the Intel Research Lab dataset. ...
doi:10.1007/s13218-010-0034-2
fatcat:t4ygjusjrjejbmpmbezzcmodva
Map building without localization by dimensionality reduction techniques
2007
Proceedings of the 24th international conference on Machine learning - ICML '07
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Not only traditional linear PCA but also recent manifold learning techniques can be used for solving this problem. ...
In contrast to the SLAM framework, LFMDR framework does not require localization procedures nor explicit measurement and motion models. ...
Acknowledgments The author would like to thank T-PRIMAL (Tokyo PRobabilistic Inference and MAchine Learning) members and the ICML reviewers for valuable comments. ...
doi:10.1145/1273496.1273631
dblp:conf/icml/Yairi07
fatcat:x7pziojcbrbvtd2biaasndrmou
Enhanced hyperpolarized chemical shift imaging based on a priori segmented information
2019
Magnetic Resonance in Medicine
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2018 pre-print arXiv:1811.09370v1 fatcat:ugjtl3wah5bvrfa5avdguaftly
The purpose of the study was to develop an approach for improving the resolution and sensitivity of hyperpolarized 13 C MRSI based on a priori anatomical information derived from featured, water-based ...
We are grateful to Dr. Nava Nevo (WIS) for initial help in preparing and handling the animals, to Dr. Tangi Roussel (Neurospin) for Paravision programming assistance, and to Drs. ...
Figure 7 shows results from the MRSI study reported as #2 in Supporting Information Figure S2 , only this time focusing on the spectral range corresponding to the 13 C1-alanine being metabolically produced ...
doi:10.1002/mrm.27631
pmid:30652358
fatcat:zt675qsxk5g7dkn634v3gai5vu
Review of seakeeping criteria for container ship sustainable speed calculation in rough weather
[chapter]
2014
Maritime Technology and Engineering
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Seakeeping criteria considered in the study are slamming, deck wetness, and vertical acceleration at bow. ...
Sea states describing rough weather are given for North Atlantic sea environment according to the IACS recommendation Note No.34. ...
Example is bowflare slamming that appears on container ships which is totally different from bottom slamming and requires other approach to determining criteria. ...
doi:10.1201/b17494-142
fatcat:ufrdjp74nrfa7ofwmhk7u7uume
Undelayed 3D RO-SLAM based on Gaussian-mixture and reduced spherical parametrization
2013
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
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This paper presents an undelayed range-only simultaneous localization and mapping (RO-SLAM) based on the Extended Kalman filter. ...
The paper proposes a state vector parametrization based on Gaussian-Mixture to cope with the multi-modal nature of range-only measurements and a reduced spherical parametrization of the range sensor positions ...
INTRODUCTION Range-only simultaneous localization and mapping (RO-SLAM) is an emerging application that aims to localize a mobile system at the same time it maps the position of a set of range sensors. ...
doi:10.1109/iros.2013.6696556
dblp:conf/iros/FabresseCMO13
fatcat:a7clxzoazrhm7nstbwq5bs6pyq
Good Feature Selection for Least Squares Pose Optimization in VO/VSLAM
[article]
2019
arXiv
pre-print
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Integrating Max-logDet feature selection into a state-of-the-art visual SLAM system leads to accuracy improvements with low overhead, as demonstrated via evaluation on a public benchmark. ...
Unlike existing feature selection works that are focused on efficiency only, our method significantly improves the accuracy of pose tracking, while introducing little overhead. ...
Submatrix selection with spectral preservation has been extensively studied in the fields of computational theory and machine learning [20] , [21] , for which several matrix-revealing metrics exist to ...
arXiv:1905.07807v1
fatcat:imx5gsojfbdapiy5bls4s4jrnu
Information-theoretic compression of pose graphs for laser-based SLAM
2012
The international journal of robotics research
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Our approach estimates the mutual information between the laser measurements and the map to discard the measurements that are expected to provide only a small amount of information. ...
To maintain a sparse pose graph that allows for efficient map optimization, our approach applies an approximate marginalization technique that is based on Chow-Liu trees. ...
We would like to thank Giorgio Grisetti and Maximilian Beinhofer for fruitful discussions. Furthermore, we thank Dirk Hähnel for providing the FHW and the Intel Research Lab datasets. ...
doi:10.1177/0278364912455072
fatcat:x4vr67jnfnc6rgqsd4q6fib2hu
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