跳到主要內容

臺灣博碩士論文加值系統

(3.236.28.137) 您好!臺灣時間:2021/07/25 20:38
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:SamuelSimon
研究生(外文):Samuel Simon
論文名稱:運用移動式與固定式攝影機於大範圍環境之機器人定位及建圖系統
論文名稱(外文):Localization and Mapping for Mobile Robot Navigation Employing Onboard and Surveillance Cameras in Large-Scale Environments
指導教授:張文中
指導教授(外文):Wen-Chung Chang
口試委員:莊季高姚立德王銀添傅立成
口試委員(外文):Jih-Gau Juang`Leehter YaoYin-Tien WangLi-Chen Fu
口試日期:2012-07-26
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電機工程系研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:71
中文關鍵詞:3D VSLAM移動式機器人導航飛行機器人監控攝影機
外文關鍵詞:3D VSLAMmobile robot navigationquadcoptersurveillance camera
相關次數:
  • 被引用被引用:0
  • 點閱點閱:189
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
本論文提出一種運用於大範圍未知監視環境之高精度機器人導航與控制系統,搭配地面及飛行機器人以視覺伺服方式達成同步定位與建圖。在此系統中, 天花板上將安裝多個攝影機用於監控環境, 利用這些攝影機, 整合EKF-SLAM 可進行額外的校正,此方法將會使機器人定位和環境建圖更加精準,然後,將建圖之結果從三維轉換至二維以用於軌跡規劃,並使用Bezier曲線產生機器人的規劃軌跡,讓機器人順利行進。為了擴大監控攝影機的覆蓋範圍,我們採用裝有攝影機的飛行機器人,此飛行機器人可在空中穩定地飛行, 拍攝監控攝影機未能監控的區域, 增加監控攝影機的覆蓋範圍。此系統已於一實驗室環境實驗驗證具可行性及有效性, 並預期此架構與方法將可進一步擴展機器人於未知環境中之應用性。

This thesis presents a high-precision simultaneous localization and mapping of mobile robot in unknown large-scale surveillance environments. Utilizing ceiling-mounted PTZ surveillance cameras, additional correction step is integrated into the EKF-SLAM system to ensure high-precision localization and mapping. The 3D sparse map is transformed into 3D and 2D navigation maps. Based on the navigation maps, robot trajectory can be generated using Bezier spline curves to allow smooth movements. Effective navigation and control approach for the mobile robot is proposed to allow mobile robot to follow the generated trajectory. In order to extend the coverage area of surveillance cameras, aerial robots equipped with cameras is employed to cover un-surveillance area. Control law for the aerial robots is also applied allowing them to stabilize themselves and move around in un-surveillance area. Experiments were performed in laboratory environments to validate the feasibility and effectiveness of the proposed system. This system can be further developed to potential robotics applications in unknown environments.

CHINESE ABSTRACT .................................... i
ENGLISH ABSTRACT .................................... ii
ACKNOWLEDGEMENTS .................................... iii
TABLE OF CONTENTS ................................... iv
LIST OF FIGURES ..................................... vii

1 INTRODUCTION ...................................... 1
1.1 Background ...................................... 1
1.2 Objective ....................................... 4
1.3 Contributions of the Thesis ..................... 4
1.4 Thesis Organization ............................. 5

2 SYSTEM OVERVIEW ................................... 6
2.1 System Architecture ............................. 6
2.2 System Process .................................. 7

3 IMAGE PROCESSING .................................. 9
3.1 Feature Detection ............................... 9
3.2 Feature Descriptor .............................. 12
3.3 Feature Matching ................................ 14

4 VSLAM WITH CORRECTION USING SURVEILLANCE CAMERA ... 16
4.1 Motion Model .................................... 16
4.2 Measurement Prediction .......................... 17
4.3 EKF-SLAM ........................................ 19
4.4 Correction Using Surveillance Camera ............ 20
4.4.1 Artificial Feature ............................ 23
4.4.2 Features Database ............................. 24

5 NAVIGATION AND CONTROL LAWS ....................... 25
5.1 Navigation Map .................................. 25
5.2 Trajectory Planning ............................. 26
5.3 Mobile Robot Control Laws ....................... 27
5.3.1 Ground Mobile Robot ........................... 27
5.3.2 Aerial Robot .................................. 29

6 EXPERIMENTAL RESULTS AND ANALYSIS ................. 31
6.1 Natural Feature ................................. 32
6.2 Artificial Feature 1 ............................ 38
6.3 Artificial Feature 2 ............................ 44
6.4 Artificial Feature 3 ............................ 51
6.5 Outdoor ......................................... 57
6.6 Performance Comparison .......................... 59

7 CONCLUSIONS ....................................... 63
7.1 Summary ......................................... 63
7.2 Conclusion ...................................... 63
7.3 Future Extension ................................ 64

REFERENCES .......................................... 65
AUTHOR .............................................. 71

[1] M. Montemerlo and S. Thrun. Simultaneous localization and mapping with unknown data association using fastslam. In Robotics and Automation. Proceedings. IEEE International Conference on, volume 2, pages 19851981, September 2003.
[2] J. Civera, A. J. Davison, and J. M. M. Montiel. Inverse depth parametrization for monocular slam. IEEE Transactions on Robotic, 24(5):932945, Oct. 2008.
[3] Chieh-Chih Wang and C. Thorpe. Simultaneous localization and mapping with detection and tracking of moving objects. In Robotics and Automation. Proceedings. IEEE International Conference on, volume 3, pages 29182924, September 2002.
[4] T. Suzuki, Y. Amano, and T. Hashizume. Development of a sift based monocular ekf-slam algorithm for a small unmanned aerial vehicle. In SICE Annual Conference (SICE), 2011 Proceedings of, pages 1656 1659, sept. 2011.
[5] Christopher Mei, Eric Sommerlade, Gabe Sibley, Paul M. Newman, and Ian D. Reid. Hidden view synthesis using real-time visual slam for simplifying video surveillance analysis. In ICRA11, pages 42404245, 2011.
[6] H. Choset and K. Nagatani. Topological simultaneous localization and mapping (slam): toward exact localization without explicit localization. Robotics and Automation, IEEE Transactions on, 17(2):125137, apr 2001.
[7] K. Celik, Soon-Jo Chung, M. Clausman, and A.K. Somani. Monocular vision slam for indoor aerial vehicles. In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pages 1566 1573, oct. 2009.
[8] L. Goncalves, E. di Bernardo, D. Benson, M. Svedman, J. Ostrowski, N. Karlsson, and P. Pirjanian. A visual front-end for simultaneous localization and mapping. In Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on, pages 44 49, april 2005.
[9] N. Karlsson, E. di Bernardo, J. Ostrowski, L. Goncalves, P. Pirjanian, and M.E. Munich. The vslam algorithm for robust localization and mapping. In Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on, pages 24 29, april 2005.
[10] Jeong-Gwan Kang, Won-Seok Choi, Su-Yong An, and Se-Young Oh. Augmented ekf based slam method for improving the accuracy of the feature map. In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, pages 3725 3731, oct. 2010.
[11] A. J. Davison and D. W. Murray. Simultaneous localization and map-building using active vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7):865880, July 2002.
[12] A. J. Davison, I. Reid, N. Molton, and O. Stasse. Monoslam: real-time single camera slam. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(6):1052 1067, 2007.
[13] R. Munguia and A. Grau. Closing loops with a virtual sensor based on monocular slam. Instrumentation and Measurement, IEEE Transactions on, 58(8):2377 2384, aug. 2009.
[14] Seo-Yeon Hwang and Jae-Bok Song. Monocular vision-based slam in indoor environment using corner, lamp, and door features from upward-looking camera. Industrial Electronics, IEEE Transactions on, 58(10):4804 4812, oct. 2011.
[15] B. Steder, G. Grisetti, C. Stachniss, and W. Burgard. Visual slam for flying vehicles. Robotics, IEEE Transactions on, 24(5):1088 1093, oct. 2008.
[16] G. Silveira, E. Malis, and P. Rives. An efficient direct approach to visual slam. Robotics, IEEE Transactions on, 24(5):969 979, oct. 2008.
[17] Wen-Chung Chang. Visual simultaneous localization and mapping employing active infrared lighting. Advanced Science Letters, 8:463468, Apr. 2012.
[18] Wen-Chung Chang, Van-Truong Nguyen, and Ping-Rung Chu. Reconstruction of 3d contour with an active laser-vision robotic system. Asian Journal of Control, 14(2):400412, Mar. 2012.
[19] W.-C. Chang and P.-R. Chu. An intelligent space for mobile robot navigation with online calibrated vision sensors. In Proc. of the 11th International Conference on Control, Automation, Robotics and Vision, Singapore, Dec. 2010.
[20] Wen-Chung Chang. An on-line calibrated visual intelligent space for navigation and control of mobile robots. In Proc. of the 2009 ICROS-SICE International Joint Conference, Fukuoka, Japan, Aug 2009.
[21] F. Hashikawa and K. Morioka. Mobile robot navigation based on interactive slam with an intelligent space. In Ubiquitous Robots and Ambient Intelligence (URAI), 2011 8th International Conference on, pages 788 789, nov. 2011.
[22] H. Morioka, S. Yi, and O. Hasegawa. Vision-based mobile robots slam and navigation in crowded environments. In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages 3998 4005, sept. 2011.
[23] S. Garrido, L. Moreno, and D. Blanco. Exploration and mapping using the vfm motion planner. Instrumentation and Measurement, IEEE Transactions on, 58(8):2880 2892, aug. 2009.
[24] H. Lategahn, A. Geiger, and B. Kitt. Visual slam for autonomous ground vehicles. In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages 17321737, may 2011.
[25] H.J. Chang, C.S.G. Lee, Y.C. Hu, and Yung-Hsiang Lu. Multi-robot slam with topological/metric maps. In Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on, pages 1467 1472, 29 2007-nov. 2 2007.
[26] J.Z. Sasiadek, A. Monjazeb, and D. Necsulescu. Navigation of an autonomous mobile robot using ekf-slam and fastslam. In Control and Automation, 2008 16th Mediterranean Conference on, pages 517 522, june 2008.
[27] Yuan Long Wei and Min Cheol Lee. Mobile robot autonomous navigation using mems gyro north finding method in global urban system. In Mechatronics and Automation (ICMA), 2011 International Conference on, pages 91 96, aug. 2011.
[28] M. Miettinen, M. Ohman, A. Visala, and P. Forsman. Simultaneous localization and mapping for forest harvesters. In Robotics and Automation, 2007 IEEE International Conference on, pages 517 522, april 2007.
[29] Jianbo Shi and C. Tomasi. Good features to track. In Computer Vision and Pattern Recognition, 1994. Proceedings CVPR 94., 1994 IEEE Computer Society Conference on, pages 593 600, jun 1994.
[30] H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool. Surf: speeded up robust features. Computer Vision and Image Understanding, 110:346359, 2008.
[31] David G. Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision, 60(2):91110, November 2004.
[32] Marius Muja and David G. Lowe. Fast approximate nearest neighbors with automatic algorithm configuration. In International Conference on Computer Vision Theory and Application VISSAPP09), pages 331340. INSTICC Press, 2009.
[33] Jerome H. Friedman, Jon Louis Bentley, and Raphael Ari Finkel. An algorithm for finding best matches in logarithmic expected time. ACM Trans. Math. Softw., 3(3):209226, September 1977.
[34] H. Durrant-Whyte and T. Bailey. Simultaneous localization and mapping: part i. IEEE Transactions on Robotics and Automation Magazine, 13(2):99108, 2006.
[35] H. Durrant-Whyte and T. Bailey. Simultaneous localization and mapping: part ii. IEEE Transactions on Robotics and Automation Magazine, 13(3):108117, 2006.
[36] A.P. Gee, D. Chekhlov, A. Calway, and W. Mayol-Cuevas. Discovering higher level structure in visual slam. Robotics, IEEE Transactions on, 24(5):980 990, oct. 2008.
[37] A. Piazzi, C. Guarino Lo Bianco, and M. Romano. Splines for the smooth path generation of wheeled mobile robots. Robotics, IEEE Transactions on, 23(5):1089 1095, Oct. 2007.
[38] Ji wung Choi, R. Curry, and G. Elkaim. Path planning based on bezier curve for autonomous ground vehicles. In World Congress on Engineering and Computer Science 2008, WCECS 08. Advances in Electrical and Electronics Engineering - IAENG Special Edition of the, pages 158 166, Oct. 2008.
[39] Toma?s Krajn?k, Vojt?ech Vonasek, Daniel Fi?ser, and Jan Faigl. AR-Drone as a Platform for Robotic Research and Education. In Research and Education in Robotics: EUROBOT 2011, Heidelberg, 2011. Springer.
[40] S. Alcantara, C. Pedret, R. Vilanova, andW.D. Zhang. Setpoint-oriented robust pid tuning from a simple min-max model matching specification. In Emerging Technologies Factory Automation, 2009. ETFA 2009. IEEE Conference on, pages 1 8, sept. 2009.

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top