A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 2 Issue 2
Apr.  2015

IEEE/CAA Journal of Automatica Sinica

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    CiteScore: 11.2, Top 5% (Q1)
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Article Contents
Wei Shao, Shulin Sui, Lin Meng and Yaobin Yue, "Stable Estimation of Horizontal Velocity for Planetary Lander with Motion Constraints," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 2, pp. 198-206, 2015.
Citation: Wei Shao, Shulin Sui, Lin Meng and Yaobin Yue, "Stable Estimation of Horizontal Velocity for Planetary Lander with Motion Constraints," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 2, pp. 198-206, 2015.

Stable Estimation of Horizontal Velocity for Planetary Lander with Motion Constraints


This work was supported by National Basic Research Program of China (973 Program) (2012CB720000), National Natural Science Foundation of China (61104187) and Promotive Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (BS2012NY003).

  • The planetary lander usually selects image feature points and tracks them from frame to frame in order to determine its own position and velocity during landing. Aiming to keep features tracking in consecutive frames, this paper proposes an approach of calculating the field of view (FOV) overlapping area in a 2D plane. Then the rotational and translational motion constraints of the lander can be found. If the FOVs intersects each other, the horizontal velocity of the lander is quickly estimated based on the least square method after the ill-conditioned matrices are eliminated previously. The Monte Carlo simulation results show that the proposed approach is not only able to recover the ego-motion of planetary lander, but also improves the stabilization performance. The relationship of the estimation error, running time and number of points is shown in the simulation results as well.


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  • [1]
    Johnson A, Willson R, Goguen J, Alexander J, Meller D. Field testing of the mars exploration rovers decent image motion estimation system. In:Proceedings of the 2005 International Conference Robotics and Automation. Barcelona, Spain:IEEE, 2005. 4463-4469
    Tweddle B E. Computer Vision Based Navigation for Spacecraft Proximity Operations[Master dissertation], Massachusetts Institute of Technology, USA, 2010.
    van Pham Bach V P, Lacroix Simon L, Devy Michel D. Vision-based absolute navigation for descent and landing. Journal of Field Robotics, 2012, 29(4):627-647
    Cheng Y, Goguen J, Johnson A, Legetr C, Matthies L, Martin M S, Willson Ret al. The Mars exploration rovers descent image motion estimation system. In:Proceedings of the 2004 IEEE Intelligent Tutoring Systems, Los Alamitos, USA:IEEE, 2004. 13-21
    Johnson A, Willson R, Cheng Y, Goguen J, Leger C, Sanmartin M, Matthies Let al. Design through operation of an image-based velocity estimation system for Mars landing. International Journal of Computer Vision, 2007, 74(3):319-341
    Harris C, Stevens M. A combined corner and edge detector. In:Proceedings of the 4th Alvey Vision Conference. England:University of Manchester, 1988. 147-151
    Flandin G, Polle B, Frapard B, Vidal P, Philippe C, Voirin T. Vision based navigation for planetary exploration. In:Proceedings of the 32nd Annual AAS Rocky Mountain Guidance and Control Conference. Breckenridge, Colorado:2009. 277-296
    Lanza Piergiorgio L, Noceti Nicoletta N, Maddaleno Corrado M, Toma Antonio T, Zini Luca Z, Odone Francesca O. A vision-based navigation facility for planetary entry descent landing. In:Proceedings of the 12th International Conference on Computer Vision. Florence, Italy:Springer, 2012. 546-555
    Rigatos Gerasimos G R. Nonlinear Kalman filters and particle filters for integrated navigation of unmanned aerial vehicles. Robotics and Autonomous Systems, 2012, 60(7):978-995
    Li M Y, Mourikis Anastasion I M. High-precision, consistent EKF-based visual-inertial odometery. International Journal of Robotics Research, 2013, 32(6):690-711
    Paul A J, Lorraine E P. A historical compilation of software metrics with applicability to NASA's Orion spacecraft flight software sizing. Innovations in Systems and Software Engineering, 2011, 7(3):161-170
    Dubois M O, Parkes S, Dunstam M. Testing and validation of planetary vision-based navigation systems with PANGU. In:Proceedings of the 21st International Symposium on Space Flight Dynamics. Toulouse, France:ISSFD, 2009
    Newcombe R A, Davison A J. Live dense reconstruction with a single moving camera. In:Proceedings of the 2010 International Conference on Computer Vision and Pattern Recognition. San Francisco, USA:IEEE, 2010. 1498-1505
    Morel J M, Yu G S. ASIFT:a new framework for fully affine invariant image comparison. SIAM Journal on Imaging Sciences, 2009, 2(2):438-469
    Lowe D G. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 2004, 60(42):91-110
    Bay H, Ess A, Tuytelaars T, van Gool L V. SURF:speeded up robust features. Computer Vision and Image Understanding, 2008, 110(3):346-359
    Peris R, Marquina A, Candela V. The convergence of the perturbed Newton method and its application for ill-conditioned problems. Applied Mathematics and Computation, 2011, 218(7):2988-3001
    Salahi M. On regularization of ill-conditioned linear systems. Journal of Applied Mathematics, 2008, 5(17):43-49
    Brezinski C, Novati P, Redivo Z M. A rational Arnoldi approach for ill-conditioned linear systems. Journal of Computational and Applied Mathematics, 2012, 236(8):2063-2077


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