Abstract
This paper describes a loosely coupled approach for the improvement of state estimation in autonomous inertial navigation, using image-based relative motion estimation for augmentation. The augmentation system uses a recently proposed pose estimation technique based on a Entropy-Like cost function, which was proven to be robust to the presence of noise and outliers in the visual features. Experimental evidence of its performance is given and compared to a state-of-the-art algorithm. Vision-inertial integrated navigation is achieved using an Indirect Kalman Navigation Filter in the framework of stochastic cloning, and the proposed robust relative pose estimation technique is used to feed a relative position fix to the navigation filter. Simulation and Experimental results are presented and compared with the results obtained via the classical RANSAC – based Direct Linear Transform approach.
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Keywords
- Scale Invariant Feature Transform
- Visual Odometry
- Linear Parameter Vary
- Stereo Vision System
- Navigation Frame
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References
Broggi, A.: Robust Real-Time Lane and Road Detection in Critical Shadow Conditions. In: Proceedings of IEEE International Symposium on Computer Vision, Coral Gables, Florida (1995)
Watanabe, Y., Calise, A.J., Johnson, E.N.: Vision-Based Obstacle Avoidance for UAVs. In: AIAA Guidance, Navigation and Control Conference and Exhibit, Hilton Head, South Carolina (2007)
Pollini, L., Greco, F., Mati, R., Innocenti, M., Tortelli, A.: Stereo Vision Obstacle Detection based on Scale Invariant Feature Transform Algorithm. In: AIAA Guidance Navigation and Control Conference, Hilton Head, South Carolina (2007)
Innocenti, M., Mati, R., Pollini, L.: Vision Algorithms for Formation Flight and Aerial Refueling with Optimal Marker Labeling. In: AIAA Modeling and Simulation Technologies Conference, vol. 1, pp. 1–15 (2005)
Campa, G., Mammarella, M., Napolitano, M.R., Fravolini, M.L., Pollini, L., Stolarik, B.: A comparison of Pose Estimation algorithms for Machine Vision based Aerial Refueling for UAVs. In: Mediterranean Control Conference 2006, vol. 1, pp. 1–6 (2006)
Giulietti, F., Pollini, L., Innocenti, M., Napolitano, M.: Dynamic and control issues of formation flight. Aerospace Science and Technology 9(1), 65–71 (2005)
Pollini, L., Innocenti, M., Giulietti, F.: Formation Flight: a Behavioral Approach. In: AIAA Guidance, Navigation and Control Conference, Montreal, Canada, vol. 1 (2001)
Hartley, R.I., Kahl, F.: Optimal algorithms in multiview geometry. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part I. LNCS, vol. 4843, pp. 13–34. Springer, Heidelberg (2007)
Milella, A., Siegwart, R.: Stereo-Based Ego-Motion Estimation Using Pixel Tracking and Iterative Closest Point. In: Proceedings of the Fourth IEEE International Conference on Computer Vision Systems (2006)
Nistér, D.: Preemptive RANSAC for Live Structure and Motion Estimation. In: IEEE International Conference on Computer Vision (2003)
Olson, C.F., Matthies, L.H., Schoppers, M., Maimone, M.W.: Rover navigation using stereo ego-motion. Robotics and Autonomous Systems 43, 215–229 (2003)
Dame, A., Marchand, E.: Entropy-based visual servoing. In: IEEE International Conference on Robotics and Automation, Kobe, Japan (2009)
Jones, E., Soatto, S.: Visual-Inertial Navigation, Mapping and Localization: A Scalable Real-Time Causal Approach. International Journal of Robotics Research (2010)
Mourikis, A., Trawny, N., Roumeliotis, S., Johnson, A., Ansar, A., Matthies, L.: Vision-Aided Inertial Navigation for Spacecraft Entry, Descent, and Landing. IEEE Transactions on Robotics 25(2), 264–280 (2009)
Bryson, M., Reid, A., Ramos, F., Sukkarieh, S.: Airborne vision-based mapping and classification of large farmland environments. J. Field Robot. 27(5), 632–655 (2010)
Roumeliotis, S., Johnson, A., Montgomery, J.: Augmenting inertial navigation with image-based motion estimation. In: Proceedings of IEEE International Conference on Robotics and Automation (2002)
Tardif, J.-P., George, M., Laverne, M., Kelly, A., Stentz, A.: A new approach to vision-aided inertial navigation. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2010)
Huber, P.J., Ronchetti, E.M.: Robust Statistics, 2nd edn. John Wiley & Sons, Inc. (2009)
Konolige, K., Agrawal, M., Solà, J.: Large-Scale Visual Odometry for Rough Terrain. Robotics Research; Springer Tracts in Advanced Robotics 66, 201–212 (2011)
Roumeliotis, S., Burdick, J.: Stochastic Cloning: A generalized framework for processing relative state measurements. In: Proceedings of IEEE International Conference on Robotics and Automation (2002)
Rogers, R.: Applied Mathematics in Integrated Navigation Systems. American Institute of Aeronautics and Astronautics (2007)
Lowe, D.: Object Recognition from Local Scale-Invariant Features. In: Proc. of the International Conference on Computer Vision (ICCV) (1999)
Le, H., Kendall, D.G.: The Riemannian Structure of Euclidean Shape Spaces: A Novel Environment for Statistics. The Annals of Statistics 21(3), 1225–1271 (1993)
Indiveri, G.: An Entropy-Like Estimator for Robust Parameter Identification. Entropy 11, 560–585 (2009)
Chakrabarti, C., De, K.: Boltzmann-Gibbs entropy: axiomatic characterization and application. Journal of Mathematics and Mathematical Sciences 23(4), 243–251 (2000)
Di Corato, F., Innocenti, M., Indiveri, G., Pollini, L.: An Entropy-Like Approach to Vision Based Autonomous Navigation. In: The Proceedings of the IEEE International Conference on Robotics and Automation, Shanghai, China (2011)
Di Corato, F., Innocenti, M., Pollini, L.: An Entropy-Like Approach to Vision-Aided Inertial Navigation. In: The Proceedings of the 18th IFAC World Congress, Milan, Italy (2011)
Di Corato, F., Innocenti, M., Pollini, L.: Robust Vision-Aided Inertial Navigation via Entropy-Like Relative Pose Estimation. Journal of Gyroscopy and Navigation 4(1), 1–13 (2013)
Nistér, D., Naroditsky, O., Bergen, J.: Visual Odometry. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition (2004)
Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press (2000)
Triggs, B., McLauchlan, P.F., Hartley, R.I., Fitzgibbon, A.W.: Bundle adjustment – A modern synthesis. In: Triggs, B., Zisserman, A., Szeliski, R. (eds.) Vision Algorithms 1999. LNCS, vol. 1883, pp. 298–372. Springer, Heidelberg (2000)
Vedaldi, A., Fulkerson, B.: Vlfeat: an open and portable library of computer vision algorithms. In: Proceedings of the International Conference on Multimedia (MM 2010) (2010)
Lee, T.: Vision Lab Geometry Library. UCLA VisionLab (2008), http://vision.ucla.edu/vlg/
Innocenti, M., Pollini, L.: A Synthetic Environment for Dynamic Systems Control and Distributed Simulation. IEEE Control Systems Magazine 20(2), 49–61 (2000)
Pollini, L., Greco, F., Mati, R., Innocenti, M.: Stereo Vision Obstacle Detection based on Scale Invariant Feature Transform Algorithm. In: Guidance Navigation and Control Conference (2007)
Hornegger, J., Tomasi, C.: Representation issues in the ML estimation of camera motion. In: The Proceedings of the Seventh IEEE International Conference on Computer Vision (1999)
Schmidt, J., Niemann, H.: Using Quaternions for Parametrizing 3-D Rotations in Unconstrained Nonlinear Optimization. In: Proceedings of the Vision Modeling and Visualization Conference (2001)
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Di Corato, F., Innocenti, M., Pollini, L. (2015). Combined Vision – Inertial Navigation with Improved Outlier Robustness. In: Choukroun, D., Oshman, Y., Thienel, J., Idan, M. (eds) Advances in Estimation, Navigation, and Spacecraft Control. ENCS 2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44785-7_16
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DOI: https://doi.org/10.1007/978-3-662-44785-7_16
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