A taxonomy of vision systems for ground mobile robots

International Journal of Advanced Robotic Systems

Volumn 11, Issue 1, 2014, Pages

  Martínez Gómez, Jesus ^a   Fernández Caballero, Antonio ^a   García Varea, Ismael ^a   Rodríguez, Luis ^a   Romero González, Cristina ^a  

^a UNIVERSITY OF CASTILLA LA MANCHA   (Spain)

Author keywords

Ground Mobile Robots; Review; Taxonomy; Vision Systems

Indexed keywords

MOBILE ROBOTS; REVIEWS; ROBOTICS; TAXONOMIES;

GROUND ROBOT; MOBILE ROBOTIC; ROBOTIC VISION; STATE OF THE ART; VISION SYSTEMS;

COMPUTER VISION;

EID: 84906068620     PISSN: 17298806     EISSN: 17298814     Source Type: Journal    
DOI: 10.5772/58900     Document Type: Article

References (204)

1. A. Casals and A. Fernández-Caballero. Robotics and autonomous systems in the 50th anniversary of artificial intelligence. Robotics and Autonomous Systems, 55(12):837-839, 2007.
2. D. Kragic and M. Vincze. Vision for robotics. Foundations and Trends in Robotics, 1(1):1-78, 2009.
3. 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):865-880, 2002.
4. N. Karlsson, E. Di Bernardo, J. Ostrowski, L. Goncalves, P. Pirjanian, and M.E. Munich. The vslam algorithm for robust localization and mapping. In Proceedings of the 2005 IEEE International Conference on Robotics and Automation, pages 24-29, April 2005.
5. R. Gonzalez, F. Rodriguez, J.L. Guzman, C. Pradalier, and R. Siegwart. Combined visual odometry and visual compass for off-road mobile robots localization. Robotica, 30(6):865-878, 2012.
6. A. Torralba, K. P. Murphy, W. T. Freeman, and M. A. Rubin. Context-based vision system for place and object recognition. In Proceedings of the Ninth IEEE International Conference on Computer Vision, pages 273-280. IEEE, 2003.
7. J. Martinez-Gomez, A. Jimenez-Picazo, J. A. Gamez, and I. Garcia Varea. Combining invariant features and localization techniques for visual place classification: successful experiences in the robotvision@ imageclef competition. Journal of Physical Agents, 5(1):45-54, 2011.
8. P. Espinace, T. Kollar, N. Roy, and A. Soto. Indoor scene recognition by a mobile robot through adaptive object detection. Robotics and Autonomous Systems, 61(9):932-947, 2013.
9. Terrence Fong, Illah Nourbakhsh, and Kerstin Dautenhahn. A survey of socially interactive robots. Robotics and Autonomous Systems, 42(3):143-166, 2003.
10. L. Li, S. Yan, X. Yu, Y.K. Tan, and H. Li. Robust multiperson detection and tracking for mobile service and social robots. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42(5):1398-1412, 2012.
11. C.-W. Park and T. Lee. A robust facial feature detection on mobile robot platform. Machine Vision and Applications, 21(6):981-988, 2010.
12. José M. Gascueña, Francisco J. Garijo, Antonio Fernández-Caballero, Marie-Pierre Gleizes, and André Machonin. Deliberative control components for eldercare robot team cooperation. Journal of Intelligent and Fuzzy Systems, in press, 2014.
13. P.P. Kumar, P. Vadakkepat, and A.P. Loh. Hand posture and face recognition using a fuzzy-rough approach. International Journal of Humanoid Robotics, 7(3):331-356, 2010.
14. Y. Wakuda, K. Sekiyama, and T. Fukuda. Dynamic event interpretation and description from visual scene based on cognitive ontology for recognition by a robot. International Journal of Robotics and Automation, 24(3):263-279, 2009.
15. D. Xu, L. Han, M. Tan, and Y.F. Li. Ceiling-based visual positioning for an indoor mobile robot with monocular vision. IEEE Transactions on Industrial Electronics, 56(5):1617-1628, 2009.
16. J.P. Barreto, L. Perdigoto, R. Caseiro, and H. Araujo. Active stereo tracking of n≤3 targets using line scan cameras. IEEE Transactions on Robotics, 26(3):442-457, 2010.
17. M. Imran. Analysis of Vision Systems and Taxonomy Formulation: An Abstract Model for Generalization. Mid Sweden University, 2011.
18. M. Imran, K. Benkrid, K. Khursheed, N. Ahmad, M. O'Nils, and N. Lawal. Analysis and characterization of embedded vision systems for taxonomy formulation. In Real-Time Image and Video Processing, volume 86560J, 2013.
19. R. Gade and T. Moeslund. Thermal cameras and applications: a survey. Machine Vision and Applications, 25(1):245-262, 2014.
20. A. Torabi, G. Massé, and G. Bilodeau. An iterative integrated framework for thermal-visible image registration, sensor fusion, and people tracking for video surveillance applications. Computer Vision and Image Understanding, 116(2):210-221, 2012.
21. J. Hwang, S. Jun, S. Kim, D. Cha, K. Jeon, and J. Lee. Novel fire detection device for robotic fire fighting. In Control Automation and Systems (ICCAS), 2010 International Conference on, pages 96-100. IEEE, 2010.
22. N Memarian, T Chau, and A.N. Venetsanopoulos. Application of infrared thermal imaging in rehabilitation engineering: Preliminary results. In Science and Technology for Humanity (TIC-STH), 2009 IEEE Toronto International Conference, pages 1-5. IEEE, 2009.
23. T.R. Gault and A.A. Farag. A fully automatic method to extract the heart rate from thermal video. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on, pages 336-341. IEEE, 2013.
24. Bernd Jähne. Practical Handbook on Image Processing for Scientific Applications. CRC Press, 1997.
25. David A. Forsyth and Jean Ponce. Computer Vision: A Modern Approach. Prentice-Hall, 2002.
26. Rafael C. Gonzalez and Richard E. Woods. Digital Image Processing (3rd Edition). Prentice-Hall, 2006.
27. Maja J. Mataric. The Robotics Primer. The MIT Press, 2007.
28. R. Siegwart, I.R. Nourbakhsh, and D. Scaramuzza. Introduction to Autonomous Mobile Robots, 2nd edition. The MIT Press, 2011.
29. F. Bonin-Font, A. Ortiz, and G. Oliver. Visual navigation for mobile robots: A survey. Journal of Intelligent and Robotic Systems, 53(3):263-296, 2008.
30. M. Staniak and C. Zielinski. Structures of visual servos. Robotics and Autonomous Systems, 58(8):940-954, 2010.
31. S. Fuchs and G. Hirzinger. Extrinsic and depth calibration of tof-cameras. In 26th IEEE Conference on Computer Vision and Pattern Recognition, volume 4587828, 2008.
32. Z. Zhao and Y. Weng. A flexible method combining camera calibration and hand-eye calibration. Robotica, 31(5):747-756, 2013.
33. Zhengyou Zhang. Camera calibration with one-dimensional objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(7):892-899, 2004.
34. L. Krüger and C. Wöhler. Accurate chequerboard corner localisation for camera calibration. Pattern Recognition Letters, 32(10):1428-1435, 2011.
35. Q. Wang, L. Fu, and Z. Liu. Review on camera calibration. In 2010 Chinese Control and Decision Conference, pages 3354-3358, 2010.
36. A.S. Huang, E. Antone, M. Olson, L. Fletcher, D. Moore, S. Teller, and J. Leonard. A high-rate, heterogeneous data set from the darpa urban challenge. International Journal of Robotics Research, 29(13):1595-1601, 2010.
37. T. Peynot, S. Scheding, and S. Terho. The marulan data sets: Multi-sensor perception in a natural environment with challenging conditions. International Journal of Robotics Research, 29(13):1602-1607, 2010.
38. C. Tomasi. Early vision. In Encyclopedia of Cognitive Sciences. Nature Publishing Group, 2002.
39. V.J. Traver and A. Bernardino. A review of log-polar imaging for visual perception in robotics. Robotics and Autonomous Systems, 58(4):378-398, 2010.
40. A. Fernández-Caballero, J.C. Castillo, J. Martínez-Cantos, and R. Martínez-Tomás. Optical flow or image subtraction in human detection from infrared camera on mobile robot. Robotics and Autonomous Systems, 58(12):1273-1281, 2010.
41. J. Pavón, J.J. Gómez-Sanz, A. Fernández-Caballero, and J.J. Valencia-Jiménez. Development of intelligent multisensor surveillance systems with agents. Robotics and Autonomous Systems, 55(12):892-903, 2007.
42. M. Bertero, T.A. Poggio, and V. Torre. Ill-posed problems in early vision. Proceedings of the IEEE, 76(8):869-889, 1988.
43. G. Cannata and M. Maggiali. Models for the design of bioinspired robot eye. IEEE Transactions on Robotics, 24(1):27-44, 2008.
44. S. Chen, Y. Li, and N.M. Kwok. Active vision in robotic systems: A survey of recent developments. International Journal of Robotics Research, 30(11):1343-1377, 2011.
45. M. Sridharan and P. Stone. Color learning and illumination invariance on mobile robots: A survey. Robotics and Autonomous Systems, 57(6-7):629-644, 2009.
46. K. Shubina and J.K. Tsotsos. Visual search for an object in a 3d environment using a mobile robot. Computer Vision and Image Understanding, 114(5):535-547, 2010.
47. A. Andreopoulos, S. Hasler, H. Wersing, H. Janssen, J.K. Tsotsos, and E. Körner. Active 3d object localization using a humanoid robot. IEEE Transactions on Robotics, 27(1):47-64, 2011.
48. S. Montabone and A. Soto. Human detection using a mobile platform and novel features derived from a visual saliency mechanism. Image and Vision Computing, 28(3):391-402, 2010.
49. G. Aragon-Camarasa, H. Fattah, and J.P. Siebert. Towards a unified visual framework in a binocular active robot vision system. Robotics and Autonomous Systems, 58(3):276-286, 2010.
50. S.Y. Chen. Kalman filter for robot vision: A survey. IEEE Transactions on Industrial Electronics, 59(11):4409-4420, 2012.
51. C.E. Agüero, F. Martín, L. Rubio, and J.M. Cañas. Comparison of smart visual attention mechanisms for humanoid robots. International Journal of Advanced Robotic Systems, 9(6):article number 233, 2012.
52. Hugh Durrant-Whyte and ThomasC. Henderson. Multisensor data fusion. In Bruno Siciliano and Oussama Khatib, editors, Springer Handbook of Robotics, pages 585-610. Springer Berlin Heidelberg, 2008.
53. J. Solá, A. Monin, M. Devy, and T. Vidal-Calleja. Fusing monocular information in multicamera slam. IEEE Transactions on Robotics, 24(5):958-968, 2008.
54. L. Susperregi, A. Arruti, E. Jauregi, B. Sierra, J.M. Martínez-Otzeta, E. Lazkano, and A. Ansuategui. Fusing multiple image transformations and a thermal sensor with kinect to improve person detection ability. Engineering Applications of Artificial Intelligence, 26(8):1980-1991, 2013.
55. G.L. Mariottini, S. Scheggi, B. Morbidi, and D. Prattichizzo. An accurate and robust visual-compass algorithm for robot-mounted omnidirectional cameras. Robotics and Autonomous Systems, 60(9):1179-1190, 2012.
56. J.-Y. Choi and S.-G. Kim. Study on the localization improvement of the dead reckoning using the ins calibrated by the fusion sensor network information. Journal of Institute of Control, Robotics and Systems, 18(8):744-749, 2013.
57. C. Premebida and U. Nunes. Fusing lidar, camera and semantic information: A context-based approach for pedestrian detection. International Journal of Robotics Research, 32(3):371-384, 2013.
58. R.G. Brown and B.R. Donald. Mobile robot self-localization without explicit landmarks. Algorithmica, 26:515-559, 2000.
59. C. Yi, Y.C. Oh, I.H. Suh, and B.-U. Choi. Indoor place classification using robot behavior and vision data. International Journal of Advanced Robotic Systems, 8(5):49-60, 2011.
60. S.-Y. Park, S.-I. Choi, J.-S. Jang, S.K. Jung, J. Kim, and J.S. Chae. Localization of unmanned ground vehicle using 3d registration of dsm and multiview range images: Application in virtual environment. Journal of Institute of Control, Robotics and Systems, 15(7):700-710, 2009.
61. M.Y. Kim, S.T. Ahn, and H. Cho. Bayesian sensor fusion of monocular vision and laser structured light sensor for robust localization of a mobile robot. Journal of Institute of Control, Robotics and Systems, 16(4):381-390, 2010.
62. Y. Feng, J. Ren, J. Jiang, M. Halvey, and J.M. Jose. Effective venue image retrieval using robust feature extraction and model constrained matching for mobile robot localization. Machine Vision and Applications, 23(5):1011-1027, 2012.
63. O. Booij, Z. Zivkovic, and B. Kröse. Efficient data association for view based slam using connected dominating sets. Robotics and Autonomous Systems, 57(12):1225-1234, 2009.
64. J. Kim, M.-S. Lim, and J. Lim. Omni camera vision-based localization for mobile robots navigation using omni-directional images. Journal of Institute of Control, Robotics and Systems, 17(3):206-210, 2011.
65. Sebastian Thrun. Robotic Mapping: A Survey. Technical Report, Carnegie-Mellon University, 2002.
66. M.-H. Li, B.-R. Hong, Z.-S. Cai, S.-H. Piao, and Q.-C. Huang. Novel indoor mobile robot navigation using monocular vision. Engineering Applications of Artificial Intelligence, 21(3):485-497, 2008.
67. S. Almansa-Valverde, J.C. Castillo, and A. Fernández-Caballero. Mobile robot map building from time-of-flight camera. Expert Systems with Applications, 39(10):8835-8843, 2012.
68. R. Ross, A. Martchenko, and J. Devlin. A 3-degree of freedom binary search pose estimation techniqu. Machine Vision and Applications, 24(4):769-776, 2013.
69. P. Henry, M. Krainin, E. Herbst, X. Ren, and D. Fox. Rgb-d mapping: Using kinect-style depth cameras for dense 3d modeling of indoor environments. International Journal of Robotics Research, 31(5):647-663, 2012.
70. S. Kim and S.-Y. Oh. Slam in indoor environments using omni-directional vertical and horizontal line features. Journal of Intelligent and Robotic Systems, 51(1):31-43, 2008.
71. D. Schleicher, L.M. Bergasa, M. Ocaña, R. Barea, and E. López. Real-time hierarchical stereo visual slam in large-scale environments. Robotics and Autonomous Systems, 58(8):991-1002, 2010.
72. A. Chatterjee, O. Ray, A. Chatterjee, and A. Rakshit. Development of a real-life ekf based slam system for mobile robots employing vision sensing. Expert Systems with Applications, 38(7):8266-8274, 2011.
73. W. Maddern, M. Milford, and G. Wyeth. Cat-slam: Probabilistic localisation and mapping using a continuous appearance-based trajectory. International Journal of Robotics Research, 31(4):429-451, 2012.
74. C. Ulas and H. Temeltas. A fast and robust feature-based scan-matching method in 3d slam and the effect of sampling strategies. International Journal of Advanced Robotic Systems, 10, 2013.
75. T.-D. Vu, J. Burlet, and O. Aycard. Grid-based localization and local mapping with moving object detection and tracking. Information Fusion, 12(1):58-69, 2011.
76. K. M. Wurm, A. Hornung, M. Bennewitz, C. Stachniss, and W. Burgard. Octomap: A probabilistic, flexible, and compact 3d map representation for robotic systems. In Proc. of the ICRA 2010 workshop on best practice in 3D perception and modeling for mobile manipulation, volume 2, 2010.
77. T.T. Cocias, F. Florin Moldoveanu, and S.M. Grigorescu. Generic fitted shapes (gfs): Volumetric object segmentation in service robotics. Robotics and Autonomous Systems, 61(9):960-972, 2013.
78. D. Beale, P. Iravani, and P. Hall. Probabilistic models for robot-based object segmentation. Robotics and Autonomous Systems, 59(12):1080-1089, 2011.
79. J. Xiao, J. Zhang, B. Adler, H. Zhang, and J. Zhang. Three-dimensional point cloud plane segmentation in both structured and unstructured environments. Robotics and Autonomous Systems, 61(12):1641-1652, 2013.
80. J. Xiao, B. Adler, J. Zhang, and H. Zhang. Planar segment based three-dimensional point cloud registration in outdoor environments. Journal of Field Robotics, 30(4):552-582, 2013.
81. Y. Do. Dividing occluded humans based on an artificial neural network for the vision of a surveillance robot. Journal of Institute of Control, Robotics and Systems, 15(5):505-510, 2009.
82. V. Alvarez-Santos, X.M. Pardo, R. Iglesias, A. Canedo-Rodriguez, and C.V. Regueiro. Feature analysis for human recognition and discrimination: Application to a person-following behaviour in a mobile robot. Robotics and Autonomous Systems, 60(8):1021-1036, 2012.
83. J.C. Castillo, J. Serrano-Cuerda, A. Fernández-Caballero, and M.T. López. Segmenting humans from mobile thermal infrared imagery. In Bioinspired Applications in Artificial and Natural Computation, pages 334-343. Springer, 2009.
84. S. Yeom and Y.-H. Woo. Person-specific face detection in a scene with optimum composite filtering and colour-shape information. International Journal of Advanced Robotic Systems, 10:70, 2013.
85. J. Zhang, J. Zhang, and S. Chen. Discover novel visual categories from dynamic hierarchies using multimodal attributes. IEEE Transactions on Industrial Informatics, 9(3):1688-1696, 2013.
86. M. Mata, J.M. Armingol, J. Fernández, and A. De La Escalera. Object learning and detection using evolutionary deformable models for mobile robot navigation. Robotica, 26(1):99-107, 2008.
87. N. Weiss. Adaptive supervision of moving objects for mobile robotics applications. Robotics and Autonomous Systems, 57(10):982-995, 2009.
88. J. Ma, T.H. Chung, and J. Burdick. A probabilistic framework for object search with 6-dof pose estimation. International Journal of Robotics Research, 30(10):1209-1228, 2011.
89. B. Willimon, S. Birchfield, and I. Walker. Interactive perception of rigid and non-rigid objects. International Journal of Advanced Robotic Systems, 9:227, 2012.
90. D. Gálvez-López and J.D. Tardós. Bags of binary words for fast place recognition in image sequences. IEEE Transactions on Robotics, 28(5):1188-1197, 2012.
91. F. Marino, P. De Ruvo, G. De Ruvo, M. Nitti, and E. Stella. Hiper 3-d: An omnidirectional sensor for high precision environmental 3-d reconstruction. IEEE Transactions on Industrial Electronics, 59(1):579-591, 2012.
92. D. Amarasinghe, G.K.I. Mann, and R.G. Gosine. Landmark detection and localization for mobile robot applications: A multisensor approach. Robotica, 28(5):663-673, 2010.
93. J. Leitner, S. Harding, M. Frank, A. Förster, and J. Schmidhuber. Learning spatial object localization from vision on a humanoid robot. International Journal of Advanced Robotic Systems, 9:243, 2012.
94. F. Janabi-Sharifi and M. Marey. A kalman-filter-based method for pose estimation in visual servoing. IEEE Transactions on Robotics, 26(5):939-947, 2010.
95. B. Browning, J.E. Deschaud, D. Prasser, and P. Rander. 3d mapping for high-fidelity unmanned ground vehicle lidar simulation. International Journal of Robotics Research, 31(12):1349-1376, 2012.
96. E. Chinellato, B.J. Grzyb, and A.P. Del Pobil. Pose estimation through cue integration: A neuroscience-inspired approach. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42(2):530-538, 2012.
97. J.M. Rendón-Mancha, A. Cárdenas, M.A. García, E. González-Galván, and B. Lara. Robot positioning using camera-space manipulation with a linear camera model. IEEE Transactions on Robotics, 26(4):726-733, 2010.
98. A. Ranganathan. Pliss: labeling places using online changepoint detection. Autonomous Robots, 32(4):351-368, 2012.
99. S.M. Grigorescu, G. Macesanu, T.T. Cocias, D. Puiu, and F. Moldoveanu. Robust camera pose and scene structure analysis for service robotics. Robotics and Autonomous Systems, 59(11):899-909, 2011.
100. M. Gauss, A. Buerkle, T. Laengle, J. Woern, J. Stelter, S. Ruhmkorf, and R. Middelmann. Adaptive robot based visual inspection of complex parts. In Proceedings of the 34th International Symposium on Robotics, pages 1-9, 2003.
101. J.-O. Kim and D.-J. Park. Development of a vision-based crack detection algorithm for bridge inspection. Journal of Institute of Control, Robotics and Systems, 14(7):642-646, 2008.
102. C. Choi, B. Park, H. Jung, and S. Jung. Inch-worm robot with automatic pipe tracking capability for the feeder pipe inspection of a phwr. Journal of Institute of Control, Robotics and Systems, 14(2):125-132, 2008.
103. K. Kawasue and T. Komatsu. Shape measurement of a sewer pipe using a mobile robot with computer vision. International Journal of Advanced Robotic Systems, 10:article number 52, 2013.
104. M. Baumann, S. Léonard, E.A. Croft, and J.J. Little. Path planning for improved visibility using a probabilistic road map. IEEE Transactions on Robotics, 26(1):195-200, 2010.
105. E.-H. Son, Y.-C. Kim, and K.-T. Chong. Implementation of path finding method using 3d mapping for autonomous robotic. Journal of Institute of Control, Robotics and Systems, 14(2):168-177, 2008.
106. V.N. Murali and S.T. Birchfield. Autonomous exploration using rapid perception of low-resolution image information. Autonomous Robots, 32(2):115-128, 2012.
107. M.-S. Chang and J.-H. Chou. A novel machine vision-based mobile robot navigation system in an unknown environment. International Journal of Robotics and Automation, 25(4):344-351, 2010.
108. I. Okawa and K. Nonaka. Optimal online generation of obstacle avoidance trajectory running on a low speed embedded cpu for vehicles. In Proceedings of the IEEE International Conference on Control Applications, pages 1257-1262, 2010.
109. T.K. Kang, I.-H. Choi, G.-T. Park, and M.-T. Lim. Local environment recognition system using modified surf-based 3d panoramic environment map for obstacle avoidance of a humanoid robot. International Journal of Advanced Robotic Systems, 10:275, 2013.
110. B.-S. Jeon, D.-Y. Lee, I.-H. Choi, Y.-H. Mo, J.-M. Park, and M.-T. Lim. Obstacle avoidance method for multi-agent robots using ir sensor and image information. Journal of Institute of Control, Robotics and Systems, 18(12):1122-1131, 2012.
111. Panagiotis Papadakis. Terrain traversability analysis methods for unmanned ground vehicles: A survey. Engineering Applications of Artificial Intelligence, 26(4):1373-1385, 2013.
112. W.L.D. Lui and R. Jarvis. Eye-full tower: A gpu-based variable multibaseline omnidirectional stereovision system with automatic baseline selection for outdoor mobile robot navigation. Robotics and Autonomous Systems, 58(6):747-761, 2010.
113. C. Rasmussen. Roadcompass: following rural roads with vision + ladar using vanishing point tracking. Autonomous Robots, 25(3):205-229, 2008.
114. E. Perez, C. Soria, O. Nasisi, T.F. Bastos, and V. Mut. Robotic wheelchair controlled through a vision-based interface. Robotica, 30(5):691-708, 2012.
115. R. Rodrigo, M. Zouqi, Z. Chen, and J. Samarabandu. Robust and efficient feature tracking for indoor navigation. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 39(3):658-671, 2009.
116. M. Lourenco, J.P. Barreto, and F. Vasconcelos. Srd-sift: Keypoint detection and matching in images with radial distortion. IEEE Transactions on Robotics, 28(3):752-760, 2012.
117. N. Greggio, A. Bernardino, C. Laschi, J. Santos-Victor, and P. Dario. Real-time 3d stereo tracking and localizing of spherical objects with the icub robotic platform. Journal of Intelligent & Robotic Systems, 63(3-4):417-446, 2011.
118. J.M. Gascueña and A. Fernández-Caballero. Agent-oriented modeling and development of a person-following mobile robot. Expert Systems with Applications, 38(4):4280-4290, 2011.
119. E. Petrovic, A. Leu, D. Ristic-Durrant, and V. Nikolic. Stereo vision-based human tracking for robotic follower. International Journal of Advanced Robotic Systems, 10:article number 230, 2013.
120. Christopher Nielsen, Cameron Fulford, and Manfredi Maggiore. Path following using transverse feedback linearization: Application to a maglev positioning system. Automatica, 46:585-590, 2010.
121. J. Park, W. Hwang, H. Kwon, K. Kim, and D.-I.D. Cho. A novel line of sight control system for a robot vision tracking system, using vision feedback and motion-disturbance feedforward compensation. Robotica, 31(1):99-112, 2013.
122. Z. Chen and S.T. Birchfield. Qualitative vision-based path following. IEEE Transactions on Robotics, 25(3):749-754, 2009.
123. R. Dahmouche, N. Andreff, Y. Mezouar, O. Ait-Aider, and P. Martinet. Dynamic visual servoing from sequential regions of interest acquisition. International Journal of Robotics Research, 31(4):520-537, 2012.
124. H. Wang, Y.-H. Liu, and D. Zhou. Adaptive visual servoing using point and line features with an uncalibrated eye-in-hand camera. IEEE Transactions on Robotics, 24(4):843-857, 2008.
125. E. Tatlicioglu, D.M. Dawson, and B. Xian. Adaptive visual servo regulation control for camera-in-hand configuration with a fixed camera extension. International Journal of Robotics and Automation, 24(4):346-355, 2009.
126. J. Lee and J.M. Lee. A study on the visual servoing of autonomous mobile inverted pendulum. Journal of Institute of Control, Robotics and Systems, 19(3):240-247, 2013.
127. G.L. Mariottini and D. Prattichizzo. Image-based visual servoing with central catadioptric cameras. International Journal of Robotics Research, 27(1):41-56, 2008.
128. N. Kumar, P. N. Belhumeur, A. Biswas, D. W. Jacobs, W. J. Kress, I. C. Lopez, and J.V. Soares. Leafsnap: A computer vision system for automatic plant species identification. In Computer Vision-ECCV 2012, pages 502-516. Springer, 2012.
129. T. Jaeggli, E. Koller-Meier, and L. Van Gool. Learning generative models for multi-activity body pose estimation. International Journal of Computer Vision, 83(2):121-134, 2009.
130. H. Kitano, M. Asada, Y. Kuniyoshi, I. Noda, and E. Osawa. Robocup: The robot world cup initiative. In Proceedings of the First International Conference on Autonomous Agents, pages 340-347. ACM, 1997.
131. P. Khandelwal and P. Stone. A low cost ground truth detection system for robocup using the kinect. In RoboCup 2011: Robot Soccer World Cup XV, pages 515-527. Springer, 2012.
132. H. Kato and M. Billinghurst. Marker tracking and hmd calibration for a video-based augmented reality conferencing system. In Proceedings of the 2nd IEEE and ACM International Workshop on Augmented Reality, pages 85-94. IEEE, 1999.
133. Olson E. AprilTag: A robust and flexible visual fiducial system. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 3400-3407. IEEE, May 2011.
134. S. Ceriani, G. Fontana, A. Giusti, D. Marzorati, M. Matteucci, D. Migliore, D. Rizzi, D.G. Sorrenti, and P. Taddei. Rawseeds ground truth collection systems for indoor self-localization and mapping. Autonomous Robots, 27(4):353-371, 2009.
135. M. J. Swain and D. H. Ballard. Color indexing. International Journal of Computer Vision, 7(1):11-32, 1991.
136. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In Proceedings of the IEEE Computer Society Conference on Vision and Pattern Recognition, volume 1, pages 886-893 vol. 1, 2005.
137. O. Linde and T. Lindeberg. Object recognition using composed receptive field histograms of higher dimensionality. In Proceedings of the 17th International Conference on Pattern Recognition, volume 2, pages 1-6 Vol.2, 2004.
138. Felix W., Joaquin S., and Frederic D. M. Automatic place determination using colour histograms and self-organising maps. pages 111-116, 2007.
139. T. Tuytelaars and K. Mikolajczyk. Local invariant feature detectors: a survey. Foundations and Trends® in Computer Graphics and Vision, 3(3):177-280, 2008.
140. K. Mikolajczyk and C. Schmid. Indexing based on scale invariant interest points. In Proceedings of the Eighth IEEE International Conference on Computer Vision, volume 1, pages 525-531 vol.1, 2001.
141. T. Ojala, M. Pietikainen, and T. Maenpaa. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7):971-987, 2002.
142. D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91-110, 2004.
143. H. Bay, T. Tuytelaars, and L. Van Gool. Surf: Speeded up robust features. In Computer Vision-ECCV 2006, pages 404-417. Springer, 2006.
144. E Rosten, R Porter, and T Drummond. Faster and better: A machine learning approach to corner detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(1):105-119, 2010.
145. M. Calonder, V. Lepetit, C. Strecha, and P. Fua. Brief: Binary robust independent elementary features. In 11th European Conference on Computer Vision, pages 778-792. Springer, 2010.
146. S. Leutenegger, M. Chli, and R.Y. Siegwart. Brisk: Binary robust invariant scalable keypoints. In 2011 IEEE International Conference on Computer Vision, pages 2548-2555. IEEE, 2011.
147. E. Rublee, V. Rabaud, K. Konolige, and G. Bradski. Orb: an efficient alternative to sift or surf. In 2011 IEEE International Conference on Computer Vision, pages 2564-2571. IEEE, 2011.
148. M. Jüngel, J. Hoffmann, and M. Lötzsch. A real-time auto-adjusting vision system for robotic soccer. In RoboCup 2003: Robot Soccer World Cup VII, pages 214-225. Springer, 2004.
149. R.A. Palma-Amestoy, P.A. Guerrero, P.A. Vallejos, and J. Ruiz-del Solar. Context-dependent color segmentation for aibo robots. In Proceedings of the IEEE 3rd Latin American Robotics Symposium, pages 128-136. IEEE, 2006.
150. R.B. Rusu, N. Blodow, and M. Beetz. Fast point feature histograms (fpfh) for 3d registration. In IEEE International Conference on Robotics and Automation, pages 3212-3217. IEEE, 2009.
151. B. Steder, R.B. Rusu, K. Konolige, and W. Burgard. Point feature extraction on 3d range scans taking into account object boundaries. In 2011 IEEE International Conference on Robotics and Automation, pages 2601-2608. IEEE, 2011.
152. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 2, pages 2169-2178. IEEE, 2006.
153. A. Vedaldi, V. Gulshan, M. Varma, and A. Zisserman. Multiple kernels for object detection. In Proceedings of the IEEE 12th International Conference on Computer Vision, pages 606-613. IEEE, 2009.
154. J. Liu and M. Shah. Learning human actions via information maximization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 1-8. IEEE, 2008.
155. A. Bosch, A. Zisserman, and X. Muñoz. Scene classification using a hybrid generative/discriminative approach. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(4):712-727, 2008.
156. I. Jolliffe. Principal component analysis. Wiley Online Library, 2005.
157. X. Niyogi. Locality preserving projections. In Neural information processing systems, volume 16, page 153, 2004.
158. Y.Y. Lin, T.L. Liu, and C.S. Fuh. Multiple kernel learning for dimensionality reduction. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 33(6):1147-1160, 2011.
159. C. Siagian and L. Itti. Rapid biologically-inspired scene classification using features shared with visual attention. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(2):300-312, 2007.
160. R. Rifkin and A. Klautau. In defense of one-vs-all classification. The Journal of Machine Learning Research, 5:101-141, 2004.
161. G. Tsoumakas and I. Katakis. Multi-label classification: an overview. International Journal of Data Warehousing and Mining, 3(3):1-13, 2007.
162. S. Nowak and M. J. Huiskes. New strategies for image annotation: Overview of the photo annotation task at imageclef 2010. In CLEF (Notebook Papers/LABs/Workshops), volume 1, page 4. Citeseer, 2010.
163. B.C. Russell, W.T. Freeman, A.A. Efros, J. Sivic, and A. Zisserman. Using multiple segmentations to discover objects and their extent in image collections. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 2, pages 1605-1614. IEEE, 2006.
164. M.J. Huiskes and M.S. Lew. The mir flickr retrieval evaluation. In Proceedings of the 1st ACM International Conference on Multimedia Information Retrieval, pages 39-43. ACM, 2008.
165. T. Cover and P. Hart. Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13(1):21-27, 1967.
166. W. S. Cleveland and C. Loader. Smoothing by local regression: Principles and methods. In Statistical Theory and Computational Aspects of Smoothing, pages 10-49. Springer, 1996.
167. A. C. Berg, T. L. Berg, and J. Malik. Shape matching and object recognition using low distortion correspondences. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, pages 26-33. IEEE, 2005.
168. N. Friedman, D. Geiger, and M. Goldszmidt. Bayesian network classifiers. Machine Learning, 29(2-3):131-163, 1997.
169. R. P. S. Mahler. Statistical multisource-multitarget information fusion, volume 685. Artech House Boston, 2007.
170. R. E. Kalman. A new approach to linear filtering and prediction problems. Journal of Basic Engineering, 82(1):35-45, 1960.
171. Frank Dellaert, Dieter Fox, Wolfram Burgard, and Sebastian Thrun. Monte carlo localization for mobile robots. In Proceedings of the IEEE International Conference on Robotics and Automation, volume 2, pages 1322-1328. IEEE, 1999.
172. S. Huang and G. Dissanayake. Convergence and consistency analysis for extended kalman filter based slam. IEEE Transactions on Robotics, 23(5):1036-1049, 2007.
173. D. Angelova and L. Mihaylova. Extended object tracking using monte carlo methods. IEEE Transactions on Signal Processing, 56(2):825-832, 2008.
174. L. Fei-Fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories. Computer Vision and Image Understanding, 106(1):59-70, 2007.
175. L.F. Posada, K.K. Narayanan, F. Hoffmann, and T. Bertram. Floor segmentation of omnidirectional images for mobile robot visual navigation. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 804-809. IEEE, 2010.
176. Vladimir Vapnik. The Nature of Statistical Learning Theory. Springer, 2000.
177. R. Pelossof, A. Miller, P. Allen, and T. Jebara. An svm learning approach to robotic grasping. In Proceedings of the IEEE International Conference on Robotics and Automation, volume 4, pages 3512-3518. IEEE, 2004.
178. Junji Satake and Jun Miura. Robust stereo-based person detection and tracking for a person following robot. In ICRA Workshop on People Detection and Tracking, 2009.
179. J. Luo, A. Pronobis, B. Caputo, and P. Jensfelt. Incremental learning for place recognition in dynamic environments. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 721-728. IEEE, 2007.
180. E. Hayashi and T. Kinoshita. Development of an indoor navigation system for a monocular-vision-based autonomous mobile robot. Artificial Life and Robotics, 14(3):324-328, 2009.
181. Z. Zhou, T. Chen, D. Wu, and C. Yu. Corridor navigation and obstacle distance estimation for monocular vision mobile robots. International Journal of Digital Content Technology and its Applications, 5(3):192-202, 2011.
182. H. Chen, D. Sun, J. Yang, and J. Chen. Localization for multirobot formations in indoor environment. IEEE/ASME Transactions on Mechatronics, 15(4):561-574, 2010.
183. M. Marrón-Romera, J.C. García, M.A. Sotelo, D. Pizarro, M. Mazo, J.M. Cañas, C. Losada, and A. Marcos. Stereo vision tracking of multiple objects in complex indoor environments. Sensors, 10(10):8865-8887, 2010.
184. J. Martinez and B. Caputo. Towards semi-supervised learning of semantic spatial concepts for mobile robots. Journal of Physical Agents, 4(3):19-31, 2010.
185. S.S. Srinivasa, D. Ferguson, C.J. Helfrich, D. Berenson, A. Collet, R. Diankov, G. Gallagher, G. Hollinger, J. Kuffner, and M.V. Weghe. Herb: A home exploring robotic butler. Autonomous Robots, 28(1):5-20, 2010.
186. W. Budiharto, A. Santoso, D. Purwanto, and A. Jazidie. A new method of obstacle avoidance for service robots in indoor environments. ITB Journal of Engineering Science, 44 B(2):148-167, 2012.
187. C. Hu, X. Ma, X. Dai, and K. Qian. Reliable people tracking approach for mobile robot in indoor environments. Robotics and Computer-Integrated Manufacturing, 26(2):174-179, 2010.
188. B. Caputo, H. Muller, B. Thomee, M. Villegas, R. Paredes, D. Zellhofer, H. Goeau, A. Joly, P. Bonnet, J. Martinez-Gomez, et al. Imageclef 2013: the vision, the data and the open challenges. In Information Access Evaluation. Multilinguality, Multimodality, and Visualization, pages 250-268. Springer, 2013.
189. Y. Morales, A. Carballo, E. Takeuchi, A. Aburadani, and T. Tsubouchi. Autonomous robot navigation in outdoor cluttered pedestrian walkways. Journal of Field Robotics, 26(8):609-635, 2009.
190. W.H. Huang, M. Ollis, M. Happold, and B.A. Stancil. Image-based path planning for outdoor mobile robots. Journal of Field Robotics, 26(2):196-211, 2009.
191. J. Courbon, Y. Mezouar, and P. Martinet. Autonomous navigation of vehicles from a visual memory using a generic camera model. IEEE Transactions on Intelligent Transportation Systems, 10(3):392-402, 2009.
192. H.Y. Jeon, L.F. Tian, and H. Zhu. Robust crop and weed segmentation under uncontrolled outdoor illumination. Sensors, 11(6):6270-6283, 2011.
193. A. Hornung, M. Bennewitz, and H. Strasdat. Efficient vision-based navigation. Autonomous Robots, 29(2):137-149, 2010.
194. T. Krajník, J. Faigl, V. Vonásek, K. Kosnar, M. Kulich, and L. Preucil. Simple yet stable bearing-only navigation. Journal of Field Robotics, 27(5):511-533, 2010.
195. Y. Xue, G. Tian, B. Song, and T. Zhang. Distributed environment representation and object localization system in intelligent space. Journal of Control Theory and Applications, 10(3):371-379, 2012.
196. G. Lin and X. Chen. A robot indoor position and orientation method based on 2d barcode landmark. Journal of Computers, 6(6):1191-1197, 2011.
197. M. Fiala. Designing highly reliable fiducial markers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(7):1317-1324, 2010.
198. F. Lamberti, A. Sanna, G. Paravati, P. Montuschi, V. Gatteschi, and C. Demartini. Mixed marker-based/marker-less visual odometry system for mobile robots. International Journal of Advanced Robotic Systems, 10, 2013.
199. A. Rusdinar, J. Kim, J. Lee, and S. Kim. Implementation of real-time positioning system using extended kalman filter and artificial landmark on ceiling. Journal of Mechanical Science and Technology, 26(3):949-958, 2012.
200. E.-J. Jung and B.-J. Yi. Task-oriented navigation algorithms for an outdoor environment with colored borders and obstacles. Intelligent Service Robotics, 6(2):69-77, 2013.
201. A. Gil, O.M. Mozos, M. Ballesta, and O. Reinoso. A comparative evaluation of interest point detectors and local descriptors for visual slam. Machine Vision and Applications, 21(6):905-920, 2010.
202. A. Gil, O. Reinoso, M. Ballesta, M. Juliá, and L. Payá. Estimation of visual maps with a robot network equipped with vision sensors. Sensors, 10(5):5209-5232, 2010.
203. S.-Y. Hwang and J.-B. Song. Monocular vision-based slam in indoor environment using corner, lamp, and door features from upward-looking camera. IEEE Transactions on Industrial Electronics, 58(10):4804-4812, 2011.
204. C. Siagian and L. Itti. Biologically inspired mobile robot vision localization. IEEE Transactions on Robotics, 25(4):861-873, 2009.