Abstract
This paper proposes a novel solution for improving visual localization in an active fashion. The solution, based on artificial potential field, associates each feature in the current image frame with an attractive or neutral potential energy. The resultant action drives the vehicle towards the goal, while still favouring feature rich areas. Experimental results with a mini quadrotor equipped with a downward looking camera assess the performance of the proposed method.
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References
Loianno, G., Watterson, M., Kumar, V.: Visual inertial odometry for quadrotors on SE(3). In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1544–1551 (2016)
Weiss, S., Achtelik, M.W., Lynen, S., Achtelik, M.C., Kneip, L., Chli, M., Siegwart, R.: Monocular vision for long-term micro aerial vehicle state estimation: a compendium. J. Field Robot. 30(5), 803–831 (2013)
Engel, J., Sturm, J., Cremers, D.: Accurate figure flying with a quadrocopter using onboard visual and inertial sensing. In: Proceedings of the Workshop on Visual Control of Mobile Robots (ViCoMoR) (in Conjunction with IROS 2012) (2012)
Mur-Artal, R., Montiel, J.M.M., Tards, J.D.: ORB-SLAM: a versatile and accurate monocular SLAM system. IEEE Trans. Robot. 31(5), 1147–1163 (2015)
Forster, C., Pizzoli, M., Scaramuzza, D.: SVO: fast semi-direct monocular visual odometry. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 15–22 (2015)
Engel, J., Koltun, V., Cremers, D.: Direct sparse odometry. In: arXiv:1607.02565 [cs.CV] (2016)
Scaramuzza, D., Fraundorfer, F.: Visual odometry [Tutorial]. IEEE Robot. Autom. Mag. 18(4), 80–92 (2011)
Davison, A.J., Murray, D.W.: Simultaneous localization and map-building using active vision. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 865–880 (2002)
Vidal-Calleja, T.A., Sanfeliu, A., Andrade-Cetto, J.: Action selection for single-camera SLAM. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 40(6), 1567–1581 (2010)
Sadat, S.A., Chutskoff, K., Jungic, D., Wawerla, J., Vaughan, R.: Feature-rich path planning for robust navigation of MAVs with Mono-SLAM. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3870–3875 (2014)
Mostegel, C., Wendel, A., Bischof, H.: Active monocular localization: towards autonomous monocular exploration for multirotor MAVs. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3848–3855 (2014)
Achtelik, M.W., Lynen, S., Weiss, S., Chli, M., Siegwart, R.: Motion- and uncertainty-aware path planning for micro aerial vehicles. J. Field Robot. 31(4), 676–698 (2014)
Costante, G., Forster, C., Delmerico, J., Valigi,P., Scaramuzza, D.: Perception-aware path planning. In: arXiv:1605.04151 [cs.RO] (conditionally accepted for IEEE Trans. on Robotics) (2016)
Khatib, O.: The potential field approach and operational space formulation in robot control. In: Narendra, K.S. (ed.) Adaptive and Learning Systems: Theory and Applications, pp. 367–377. Springer, Boston (1986)
Hoenig, W., Milanes, C., Scaria, L., Phan, T., Bolas, M., Ayanian, N.: Mixed reality for robotics. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5382–5387 (2015)
Shi, J., Tomasi, C.: Good features to track. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 593–600 (1994)
Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision, pp. 674–679 (1981)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)
Acknowledgement
R. Rodrigues, M. Basiri, and P. Miraldo were partially supported by Fundação para a Ciência e Tecnologia (FCT) project UID/EEA/50009/2013, and by FCT grant SFRH/BPD/111495/2015. P. Aguiar was partially supported by project POCI-01-0145-FEDER-006933/SYSTEC funded by FEDER funds through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) - and by national funds through FCT.
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Rodrigues, R.T., Basiri, M., Aguiar, A.P., Miraldo, P. (2018). Feature Based Potential Field for Low-Level Active Visual Navigation. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-70833-1_64
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DOI: https://doi.org/10.1007/978-3-319-70833-1_64
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