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Volumn , Issue , 2014, Pages

Batch Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression

Author keywords

[No Author keywords available]

Indexed keywords

CONTINUOUS TIME SYSTEMS; COVARIANCE MATRIX; DIFFERENTIAL EQUATIONS; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); INVERSE PROBLEMS; REGRESSION ANALYSIS; STATISTICAL TESTS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; WHITE NOISE;

EID: 85057122979     PISSN: None     EISSN: 2330765X     Source Type: Conference Proceeding    
DOI: 10.15607/RSS.2014.X.001     Document Type: Conference Paper
Times cited : (133)

References (48)
  • 2
    • 34047223252 scopus 로고    scopus 로고
    • SLAM: Part II State of the art
    • T Bailey and H Durrant-Whyte. SLAM: Part II State of the art. IEEE RAM, 13(3):108–117, 2006.
    • (2006) IEEE RAM , vol.13 , Issue.3 , pp. 108-117
    • Bailey, T1    Durrant-Whyte, H2
  • 3
    • 77955823781 scopus 로고    scopus 로고
    • A hybrid SLAM representation for dynamic marine environments
    • C Bibby and I D Reid. A hybrid SLAM representation for dynamic marine environments. In Proc. ICRA, 2010.
    • (2010) Proc. ICRA
    • Bibby, C1    Reid, I D2
  • 4
    • 85099439247 scopus 로고    scopus 로고
    • Continuous 3D scan-matching with a spinning 2D laser
    • M Bosse and R Zlot. Continuous 3D scan-matching with a spinning 2D laser. In Proc. ICRA, 2009.
    • (2009) Proc. ICRA
    • Bosse, M1    Zlot, R2
  • 5
    • 0008929564 scopus 로고
    • A solution to the general problem of multiple station analytical stereotriangulation
    • RCA-MTP data reduction tech. report no. 43, Patrick Airforce Base
    • D C Brown. A solution to the general problem of multiple station analytical stereotriangulation. RCA-MTP data reduction tech. report no. 43, Patrick Airforce Base, 1958.
    • (1958)
    • Brown, D C1
  • 6
    • 34247586702 scopus 로고    scopus 로고
    • MonoSLAM: Real-time single camera SLAM
    • A J Davison, I D Reid, N D Molton, and O Stasse. MonoSLAM: Real-time single camera SLAM. IEEE T. PAMI, 29(6):1052– 1067, 2007.
    • (2007) IEEE T. PAMI , vol.29 , Issue.6 , pp. 1052-1067
    • Davison, A J1    Reid, I D2    Molton, N D3    Stasse, O4
  • 8
    • 33750968800 scopus 로고    scopus 로고
    • Square Root SAM: Simultaneous localization and mapping via square root information smoothing
    • F Dellaert and M Kaess. Square Root SAM: Simultaneous localization and mapping via square root information smoothing. IJRR, 25(12):1181–1204, 2006.
    • (2006) IJRR , vol.25 , Issue.12 , pp. 1181-1204
    • Dellaert, F1    Kaess, M2
  • 9
    • 84873470640 scopus 로고    scopus 로고
    • Lighting-invariant visual odometry using lidar intensity imagery and pose interpolation
    • H J Dong and T D Barfoot. Lighting-invariant visual odometry using lidar intensity imagery and pose interpolation. In Proc. Field and Service Robotics, 2012.
    • (2012) Proc. Field and Service Robotics
    • Dong, H J1    Barfoot, T D2
  • 10
    • 85018145030 scopus 로고    scopus 로고
    • SLAM: Part I Essential algorithms
    • H Durrant-Whyte and T Bailey. SLAM: Part I Essential algorithms. IEEE RAM, 11(3):99–110, 2006.
    • (2006) IEEE RAM , vol.11 , Issue.3 , pp. 99-110
    • Durrant-Whyte, H1    Bailey, T2
  • 12
    • 33751004373 scopus 로고    scopus 로고
    • Exactly sparse delayed-state filters for view-based SLAM
    • R M Eustice, H Singh, and J J Leonard. Exactly sparse delayed-state filters for view-based SLAM. IEEE TRO, 22(6):1100– 1114, 2006.
    • (2006) IEEE TRO , vol.22 , Issue.6 , pp. 1100-1114
    • Eustice, R M1    Singh, H2    Leonard, J J3
  • 13
    • 34547509326 scopus 로고    scopus 로고
    • Gaussian processes for signal strength-based localization
    • B Ferris, D Hähnel, and D Fox. Gaussian processes for signal strength-based localization. In Proc. RSS, 2006.
    • (2006) Proc. RSS
    • Ferris, B1    Hähnel, D2    Fox, D3
  • 14
    • 84880865323 scopus 로고    scopus 로고
    • Wifi-SLAM using Gaussian process latent variable models
    • B Ferris, D Fox, and N Lawrence. Wifi-SLAM using Gaussian process latent variable models. In Proc. IJCAI, 2007.
    • (2007) Proc. IJCAI
    • Ferris, B1    Fox, D2    Lawrence, N3
  • 15
    • 84864477812 scopus 로고    scopus 로고
    • Continuous-time batch estimation using temporal basis functions
    • P T Furgale, T D Barfoot, and G Sibley. Continuous-time batch estimation using temporal basis functions. In Proc. ICRA, 2012.
    • (2012) Proc. ICRA
    • Furgale, P T1    Barfoot, T D2    Sibley, G3
  • 18
    • 84867116396 scopus 로고    scopus 로고
    • State-space inference for non-linear latent force models with application to satellite orbit prediction
    • J Hartikainen, M Seppänen, and S Särkkä. State-space inference for non-linear latent force models with application to satellite orbit prediction. In Proc. ICML, 2012.
    • (2012) Proc. ICML
    • Hartikainen, J1    Seppänen, M2    Särkkä, S3
  • 21
    • 58249138093 scopus 로고    scopus 로고
    • iSAM: Incremental smoothing and mapping
    • M Kaess, A Ranganathan, and R Dellaert. iSAM: Incremental smoothing and mapping. IEEE TRO, 24(6):1365–1378, 2008.
    • (2008) IEEE TRO , vol.24 , Issue.6 , pp. 1365-1378
    • Kaess, M1    Ranganathan, A2    Dellaert, R3
  • 22
    • 84856742278 scopus 로고    scopus 로고
    • iSAM2: Incremental smoothing and mapping using the Bayes tree
    • M Kaess, H Johannsson, R Roberts, V Ila, J J Leonard, and F Dellaert. iSAM2: Incremental smoothing and mapping using the Bayes tree. IJRR, 31(2):217–236, 2012.
    • (2012) IJRR , vol.31 , Issue.2 , pp. 217-236
    • Kaess, M1    Johannsson, H2    Roberts, R3    Ila, V4    Leonard, J J5    Dellaert, F6
  • 23
  • 25
    • 67650998865 scopus 로고    scopus 로고
    • GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
    • July
    • J Ko and D Fox. GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models. Autonomous Robots, 27(1):75–90, July 2009.
    • (2009) Autonomous Robots , vol.27 , Issue.1 , pp. 75-90
    • Ko, J1    Fox, D2
  • 26
    • 79951555580 scopus 로고    scopus 로고
    • Learning GP-BayesFilters via Gaussian process latent variable models
    • J Ko and D Fox. Learning GP-BayesFilters via Gaussian process latent variable models. Auton. Robots, 30(1):3–23, 2011.
    • (2011) Auton. Robots , vol.30 , Issue.1 , pp. 3-23
    • Ko, J1    Fox, D2
  • 27
    • 27844549624 scopus 로고    scopus 로고
    • Gaussian process latent variable models for visualization of high dimensional data
    • N Lawrence. Gaussian process latent variable models for visualization of high dimensional data. In Proc. NIPS, 2003.
    • (2003) Proc. NIPS
    • Lawrence, N1
  • 28
    • 79961050814 scopus 로고    scopus 로고
    • An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach
    • F Lindgren, H Rue, and J Lindström. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. J. of the Royal Stat. Society: Series B, 73(4):423–498, 2011.
    • (2011) J. of the Royal Stat. Society: Series B , vol.73 , Issue.4 , pp. 423-498
    • Lindgren, F1    Rue, H2    Lindström, J3
  • 29
    • 84898463430 scopus 로고    scopus 로고
    • Spline fusion: A continuous-time representation for visual-inertial fusion with application to rolling shutter cameras
    • S Lovegrove, A Patron-Perez, and G Sibley. Spline fusion: A continuous-time representation for visual-inertial fusion with application to rolling shutter cameras. In Proc. BMVC, 2013.
    • (2013) Proc. BMVC
    • Lovegrove, S1    Patron-Perez, A2    Sibley, G3
  • 30
    • 0031249780 scopus 로고    scopus 로고
    • Globally consistent range scan alignment for environment mapping
    • F Lu and E Milios. Globally consistent range scan alignment for environment mapping. Auton. Robots, 4(4):333–349, 1997.
    • (1997) Auton. Robots , vol.4 , Issue.4 , pp. 333-349
    • Lu, F1    Milios, E2
  • 36
    • 84867687753 scopus 로고    scopus 로고
    • Gaussian filtering and smoothing for continuous-discrete dynamic systems
    • S Särkkä and J Sarmavuori. Gaussian filtering and smoothing for continuous-discrete dynamic systems. Signal Processing, 93 (2):500–510, 2013.
    • (2013) Signal Processing , vol.93 , Issue.2 , pp. 500-510
    • Särkkä, S1    Sarmavuori, J2
  • 37
    • 85032750844 scopus 로고    scopus 로고
    • Spatiotemporal learning via infinite-dimensional Bayesian filtering and smoothing: A look at Gaussian process regression through Kalman filtering
    • S Särkkä, A Solin, and J Hartikainen. Spatiotemporal learning via infinite-dimensional Bayesian filtering and smoothing: A look at Gaussian process regression through Kalman filtering. IEEE Signal Processing Magazine, 30(4):51–61, 2013.
    • (2013) IEEE Signal Processing Magazine , vol.30 , Issue.4 , pp. 51-61
    • Särkkä, S1    Solin, A2    Hartikainen, J3
  • 38
    • 77958046923 scopus 로고    scopus 로고
    • Sliding window filter with application to planetary landing
    • G Sibley, L Matthies, and G Sukhatme. Sliding window filter with application to planetary landing. Journal of Field Robotics, 27(5):587–608, 2010.
    • (2010) Journal of Field Robotics , vol.27 , Issue.5 , pp. 587-608
    • Sibley, G1    Matthies, L2    Sukhatme, G3
  • 39
    • 0022905675 scopus 로고
    • On the representation and estimation of spatial uncertainty
    • R C Smith and P Cheeseman. On the representation and estimation of spatial uncertainty. IJRR, 5(4):56–68, 1986.
    • (1986) IJRR , vol.5 , Issue.4 , pp. 56-68
    • Smith, R C1    Cheeseman, P2
  • 40
    • 0000081872 scopus 로고
    • Estimating uncertain spatial relationships in robotics
    • Ingemar J. Cox and Gordon T. Wilfong, editors, pages Springer Verlag, New York
    • R C Smith, M Self, and P Cheeseman. Estimating uncertain spatial relationships in robotics. In Ingemar J. Cox and Gordon T. Wilfong, editors, Autonomous Robot Vehicles, pages 167–193. Springer Verlag, New York, 1990.
    • (1990) Autonomous Robot Vehicles , pp. 167-193
    • Smith, R C1    Self, M2    Cheeseman, P3
  • 44
    • 33646702871 scopus 로고    scopus 로고
    • The graph SLAM algorithm with applications to large-scale mapping of urban structures
    • S Thrun and M Montemerlo. The graph SLAM algorithm with applications to large-scale mapping of urban structures. IJRR, 25(5-6):403–429, 2006.
    • (2006) IJRR , vol.25 , Issue.5-6 , pp. 403-429
    • Thrun, S1    Montemerlo, M2
  • 46
    • 84878066259 scopus 로고    scopus 로고
    • Gaussian process Gauss-Newton for non-parametric simultaneous localization and mapping
    • C H Tong, P T Furgale, and T D Barfoot. Gaussian process Gauss-Newton for non-parametric simultaneous localization and mapping. IJRR, 32(5):507–525, 2013.
    • (2013) IJRR , vol.32 , Issue.5 , pp. 507-525
    • Tong, C H1    Furgale, P T2    Barfoot, T D3
  • 48
    • 34047263802 scopus 로고    scopus 로고
    • Exactly sparse extended information filters for feature-based SLAM
    • M R Walter, R M Eustice, and J J Leonard. Exactly sparse extended information filters for feature-based SLAM. IJRR, 26 (4):335–359, 2007.
    • (2007) IJRR , vol.26 , Issue.4 , pp. 335-359
    • Walter, M R1    Eustice, R M2    Leonard, J J3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.