- Volume 19 Issue 8
DOI QR Code
Vision-based Localization for AUVs using Weighted Template Matching in a Structured Environment
구조화된 환경에서의 가중치 템플릿 매칭을 이용한 자율 수중 로봇의 비전 기반 위치 인식
- Kim, Donghoon (Dept. of Civil and Environmental Engineering, Robotics Program, Korea Advanced Institute of Science and Technology (KAIST)) ;
- Lee, Donghwa (Dept. of Civil and Environmental Engineering, Robotics Program, Korea Advanced Institute of Science and Technology (KAIST)) ;
- Myung, Hyun (Dept. of Civil and Environmental Engineering, Robotics Program, Korea Advanced Institute of Science and Technology (KAIST)) ;
- Choi, Hyun-Taek (Ocean System Eng. Research Division, Korea Institute of Ocean Science and Technology (KIOST))
- Received : 2013.05.15
- Accepted : 2013.06.30
- Published : 2013.08.01
This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.
Grant : 고정밀 임무수행을 위한 인공 지능 기반의 수중 로봇 기술 개발
Supported by : 산업통상자원부, 한국해양연구원
- M. Caccia, "Laser-triangulation optical-correlation sensor for ROV slow motion estimation," IEEE Journal of Oceanic Engineering, vol. 31, no. 3, pp. 711-727, 2006. https://doi.org/10.1109/JOE.2005.858357
- M. Caccia, "Vision-based ROV horizontal motion control: nearseafloor experimental results," Control Engineering Practice, vol. 15, no. 6, pp. 703-714, 2007. https://doi.org/10.1016/j.conengprac.2006.05.008
- F. Ferreira, G. Veruggio, M. Caccia, and G. Bruzzone, "Real-time optical SLAM-based mosaicking for unmanned underwater vehicles," Intelligent Service Robotics, vol. 5, no. 1, pp. 55-71, 2012. https://doi.org/10.1007/s11370-011-0103-x
- K. N. Leabourne, S. M. Rock, S. D. Fleischer, and R. Burton, "Station keeping of an ROV using vision technology," Proceedings of MTS/IEEE OCEANS'97, vol. 1, pp. 634-640, 1997.
- S. Negahdaripour and P. Firoozfam, "An ROV stereovision system for ship-hull inspection," IEEE Journal of Oceanic Engineering, vol. 31, no. 3, pp. 551-564, 2006. https://doi.org/10.1109/JOE.2005.851391
- M. Nomoto and M. Hattori, "A deep ROV "DOLPHIN 3K": design and performance analysis," IEEE Journal of Oceanic Engineering, vol. 11, no. 3, pp. 373-391, 1986. https://doi.org/10.1109/JOE.1986.1145188
- L. Whitcomb, D. Yoerger, H. Singh, and J. Howland, "Advances in underwater robotic vehicles for deep ocean exploration: Navigation, control, and survey operations," Proc. of the Ninth International Symposium on Robotics Research, pp. 346-353, 1999.
- D. Yoerger, J. Newman, and J.-J. Slotine, "Supervisory control system for the jason ROV," IEEE Journal of Oceanic Engineering, vol. 11, no. 3, pp. 392-400, 1986. https://doi.org/10.1109/JOE.1986.1145191
- G. A. Hollinger, B. Englot, F. S. Hover, U. Mitra, and G. S. Sukhatme, "Active planning for underwater inspection and the benefit of adaptivity," International Journal of Robotics Research, vol. 32, no. 1, pp. 3-18, 2013. https://doi.org/10.1177/0278364912467485
- B.-H. Jun, J.-Y. Park, F.-Y. Lee, P.-M. Lee, C.-M. Lee, K. Kim, Y.-K. Lim, and J.-H. Oh, "Development of the AUV isimiand a free running test in an ocean engineering basin," Ocean Engineering, vol. 36, no. 1, pp. 2-14, 2009. https://doi.org/10.1016/j.oceaneng.2008.07.009
- A. Kim and R. Eustice, "Pose-graph visual SLAM with geometric model selection for autonomous underwater ship hull inspection," Proc. of IEEE/RSJ International Conference on Intelligent Robotics and Systems 2009, pp. 1559-1565, 2009.
- G. Marani and S. Choi, "Underwater target localization," IEEE Robotics & Automation Magazine, vol. 17, no. 1, pp. 64-70, 2010. https://doi.org/10.1109/MRA.2010.935793
- S. E. Webster, R. M. Eustice, H. Singh, and L. L. Whitcomb, "Advances in single-beacon one-way-travel-time acoustic navigation for underwater vehicles," International Journal of Robotics Research, vol. 31, no. 8, pp. 935-950, 2012. https://doi.org/10.1177/0278364912446166
- S.-C. Yu, T. Ura, T. Fujii, and H. Kondo, "Navigation of autonomous underwater vehicles based on artificial underwater landmarks," Proceedings of MTS/IEEE OCEANS 2001, pp. 409-416, 2011.
- J.-Y. Park, B.-H. Jun, P.-M. Lee, and J. Oh, "Experiments on vision guided docking of an autonomous underwater vehicle using one camera," Ocean Engineering, vol. 36, no. 1, pp. 48-61, 2009. https://doi.org/10.1016/j.oceaneng.2008.10.001
- G. Dudek, M. Jenkin, C. Prahacs, A. Hogue, J. Sattar, P. Giguere, A. German, H. Liu, S. Saunderson, A. Ripsman, S. Simhon, L.-A. Torres, E. Milios, P. Zhang, and I. Rekletis, "A visually guided swimming robot," Proc. of IEEE/RSJ International Conference on Intelligent Robotics and Systems 2005, pp. 3604-3609, 2005.
- J. Sattar and G. Dudek, "Robust servo-control for underwater robots using banks of visual filters," Proc. of IEEE International Conference on Robotics and Automation 2009, pp. 3583-3588, 2009.
- A. Negre, C. Pradalier, and M. Dunbabin, "Robust vision-based underwater homing using self-similar landmarks," Journal of Field Robotics, vol. 25, no. 6-7, pp. 360-377, 2008. https://doi.org/10.1002/rob.20246
- F. D. Maire, D. Prasser, M. Dunbabin, and M. Dawson, "A vision based target detection system for docking of an autonomous underwater vehicle," Proc. of the Australasian Conference on Robotics and Automation 2009, 2009.
- D. Lee, G. Kim, D. Kim, H. Myung, and H.-T. Choi, "Visionbased object detection and tracking for autonomous navigation of underwater robots," Ocean Engineering, vol. 48, pp. 59-68, 2012. https://doi.org/10.1016/j.oceaneng.2012.04.006
- D. Kim, D. Lee, H. Myung, and H.-T. Choi, "Object detection and tracking for autonomous underwater robots using weighted template matching," Proc. of MTS/IEEE OCEANS 2012, Yeosu, Korea, 2012.
- B. Balasuriya, M. Takai, W. Lam, T. Ura, and Y. Kuroda, "Vision based autonomous underwater vehicle navigation: underwater cable tracking," Proc. of MTS/IEEE OCEANS'97, vol. 2, pp. 1418-1424, 1997.
- F. S. Hover, R. M. Eustice, A. Kim, B. Englot, H. Johannsson, M. Kaess, and J. J. Leonard, "Advanced perception, navigation and planning for autonomous in-water ship hull inspection," International Journal of Robotics Research, vol. 31, no. 12, pp. 1445-1464, Oct. 2012. https://doi.org/10.1177/0278364912461059
- D. Park, K. Kwak, W.-K. Chung, and J. Kim, "Infrastructurebased localization system using underwater wireless sensor network," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 8, pp. 699-705, 2012. https://doi.org/10.5302/J.ICROS.2012.18.8.699
- Y.-J. Heo, G.-H. Lee, and J. Kim, "Extended Kalman filter-based localization with kinematic relationship of underwater structure inspection robots," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 19, no. 4, pp. 372-378, 2013. https://doi.org/10.5302/J.ICROS.2013.12.1837
- R. Brunelli, Template Matching Techniques in Computer Vision: Theory and Practice, Wiley, 2009.
- F. Dellaert, D. Fox, W. Burgard, and S. Thrun, "Monte Carlo localization for mobile robots," Proc. of IEEE International Conference on Robotics and Automation 1999, vol. 2, pp. 1322-1328, 1999.
- G. Dissanayake, P. Newman, S. Clark, H. F. Durrant-Whyte, and M. Csorba, "A solution to the simultaneous localisation and map building (SLAM) problem," IEEE Transactions of Robotics and Automation, vol. 17, no. 3, pp. 229-241, 2001. https://doi.org/10.1109/70.938381
- J. Aulinas, M. Carreras, X. Llado, J. Salvi, R. Garcia, R. Prados, and Y. R. Petillot, "Feature extraction for underwater visual SLAM," Proceedings of MTS/IEEE OCEANS 2011, pp. 1-7, 2011.
- J. Salvi, Y. Petillot, S. Thomas, and J. Aulinas, "Visual slam for underwater vehicles using video velocity log and natural landmarks," Proceedings of MTS/IEEE OCEANS 2008, pp. 1-6, 2008.
- H. Singh, A. Can, R. Eustice, S. Lerner, N. McPhee, O. Pizarro, and C. Roman, "Seabed AUV offers new platform for highresolution imaging," Eos, Transactions American Geophysical Union, vol. 85, no. 31, pp. 289-296, 2004.
- Z. Zhang, "A flexible new technique for camera calibration," IEEE Transactions on Pattern Analaysis, vol. 22, no. 11, pp. 1330-1334, 2000. https://doi.org/10.1109/34.888718
- C. Tomasi and R. Manduchi, "Bilateral filtering for gray and color images," Proceedings of Sixth International Conference on Computer Vision, pp. 839-846, Jan. 1998.
- D. G. Lowe, "Distinctive image features from scale-invariant keypoints," International Journal of Computer Vision, vol. 60, no. 2, pp. 91-110, 2004. https://doi.org/10.1023/B:VISI.0000029664.99615.94
- H. Bay, T. Tuytelaars, and L. Van Gool, "Surf: Speeded up robust features," Proceedings of European Conference on Computer Vision, pp. 404-417, 2006.
- K. Mikolajczyk and C. Schmid, "A performance evaluation of local descriptors," IEEE Transactions on Pattern Analysis, vol. 27, no. 10, pp. 1615-1630, 2005. https://doi.org/10.1109/TPAMI.2005.188
- N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 886-893, 2005.
- KoreaLPS, http://korealps.co.kr
- T. Fawcett, "An introduction to ROC analysis," Pattern Recognition Letters, vol. 27, no. 8, pp. 861-874, 2006. https://doi.org/10.1016/j.patrec.2005.10.010
- Vision-Based Obstacle Collision Risk Estimation of an Unmanned Surface Vehicle vol.21, pp.12, 2015, https://doi.org/10.5302/J.ICROS.2015.15.0161
- Vision-based Sensor Fusion of a Remotely Operated Vehicle for Underwater Structure Diagnostication vol.21, pp.4, 2015, https://doi.org/10.5302/J.ICROS.2015.14.8034