參考文獻 |
[1] Y. Yang and X. Zhao, “Development of a fall detection algorithm based on a tri-axial accelerometer,” in 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI), Shanghai, China, Oct. 2011, pp. 1371-1374.
[2] J. Cheng, X. Chen, and M. Shen, “A framework for daily activity monitoring and fall detection based on surface electromyography and accelerometer signals.” IEEE Journal of Biomedical and Health Informatics, vol. 17, no. 1, pp. 38-45, 2013.
[3] L. J. Kau, and C. S. Chen, “A smart phone-based pocket fall accident detection, positioning, and rescue system,” IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 1, pp. 44-56, 2015.
[4] M. Yu, A. Rhuma, S. M. Naqvi, L. Wang, and J. Chambers, “A posture recognition-based fall detection system for monitoring and elderly person in as smart home environment,” IEEE Transactions on Information Technology in Biomedicine, vol. 16, no. 6, pp. 1274-1286, 2012.
[5] E. S. L. Ho, J. C. P. Chan, D. C. K. Chan, H. P. H. Shum, Y.-M. Cheung, and P. C. Yuen, “Improving posture classification accuracy for depth sensor-based human activity monitoring in smart environments,” Computer Vision and Image Understanding, vol. 148, pp. 91-110, 2016.
[6] F. Lin, A. Wang, L. Cavuoto, and W. Wu, “Towards unobtrusive patient handling activity recognition for injury reduction among at-risk caregivers,” IEEE Journal of Biomedical and Health Informatics, Article in press.
[7] K.-T. Song and S.-C. Tsai, “Vision-based adaptive grasping of a humanoid robot arm,” in Proc. IEEE Int. Conf. Autom. Logist., Zhengzhou, China, August 2012, pp. 155-160.
[8] Y. Yang and Q.-X. Cao, “Monocular vision based 6D object localization for service robot’s intelligent grasping,” Comput. Math., vol. 64, no. 5, pp. 1235-1241, 2012.
[9] H. H. Kim, D. J. Kim, and K. H. Park, “Robust elevator button recognition in the presence of partial occlusion and clutter by specular reflections,” IEEE Transactions on Industrial Electronics, vol. 59, no. 3, pp. 1597-1611, 2012.
[10] J. Zhao, H. Zhang, Y. Liu, J. Yan, X. Zang, and Z. Zhou, “Development of the hexapod robot HITCR-II for walking on unstructured terrain,” in Proceedings of 2012 IEEE International Conference on Mechatronics and Automation, Chengdu, China, Aug. 2012, pp. 64-69.
[11] V. G. Loc, I. M. Koo, D. T. Tran, S. Park, H. Moon, and H. R. Choi, “Body workspace of quadruped walking robot and its applicability in legged locomotion,” Journal of Intelligent & Robotic Systems, vol. 67, no. 3-4, pp. 271-284, 2012.
[12] W. Wang, Z. Du and L. Sun, “Dynamic load effect on tracked robot obstacle performance,” in Proceedings of International Conference on Mechatronics, Kumamoto, Japan, May 2007, pp. 1-6.
[13] D. Choi, J. R. Kim, S. Cho, S. Jung and J. Kim, “Rocker-Pillar : Design of the Rough Terrain Mobile Robot Platform with Caterpillar Tracks and Rocker Bogie Mechanism,” in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Algarve, Portugal, Oct., 2012, pp. 3405-3410.
[14] V. G. Loc, S. G. Roh, I. M. Koo, D. T. Tran, H. M. Kim, H. Moon, and H. R. Choi, “Sensing and gait planning of quadruped walking and climbing robot for traversing in complex environment,” Robotics and Autonomous Systems, vol. 58, no. 5, pp. 666-675, 2010.
[15] D. Chugo, K. Kawabata, H. Kaetsu, H. Asama, and T. Mishima, “Terrain-surface estimation from body configurations of passive linkages,” International Journal of Advanced Robotic Systems, vol. 11, 2014.
[16] J. Sock, K. Kwak, J. Min, Y.-W. Park, “Probabilistic traversability map building for autonomous navigation,” in International Conference on Control, Automation and Systems (ICCAS 2014), Gyeonggi-do, Korea, Oct. 2014, pp. 652-655.
[17] M. Norouzi, J. V. Miro, and G. Dissanayake, “Probabilistic stable motion planning with stability uncertainty for articulated vehicles on challenging terrains,” Autonomous Robots, vol. 40, no. 2, pp. 361-381, 2016.
[18] I. H. Li, W. Y. Wang, Y. H. Chien, and N. H. Fang, “Autonomous ramp detection and climbing systems for tracked robot using Kinect sensor,” International Journal of Fuzzy Systems, vol. 15, no. 4, pp. 452-459, 2013.
[19] T. Fujita and Y. Kondo, “3D terrain measurement system with movable laser range finder,” in IEEE International Workshop on Safety, Security & Rescue Robotics (SSRR 2009), Denver, Colorado, Nov. 2009, pp. 1-6.
[20] Zenbo, https://zenbo.asus.com/
[21] C. C. Li and Y. Y. Chen, “Human posture recognition by simple rules,” in IEEE International Conference on Systems, Man and Cybernetics, Taipei, Taiwan, Oct. 2006, pp. 3237-3240.
[22] B. Boulay, F. Bremond, and M. Thonnat, “Posture recognition with a 3d human model,” in The IEE International Symposium on Imaging for Crime Detection and Prevention, London, UK, Jun. 2005, pp 135-138.
[23] B. Boulay, F. Bremond, and M. Thonnat, “Applying 3d human model in a posture recognition system,” Pattern Recognition Letters, vol. 27, no. 15, pp. 1788-1796, 2006.
[24] C. Castiello, T. D’Orazio, A. M. Fanelli, P. Spagnolo, and M. A. Torsello, “A model-free approach for posture classification,” in IEEE Conference on Advanced Video and Signal Based Surveillance, Cerno, Italy, Sep. 2005, pp. 276-281
[25] F. Xie, G. Xu, Y. Cheng, and Y. Tian, “Human body and posture recognition system based on an improved thinning algorithm,” IET Image Processing, vol. 5, no. 5, pp. 420-428, 2011.
[26] H. Fujiyoshi and A. J. Lipton, “Real-time human motion analysis by image skeletonization,” in IEEE Workshop on Applications of Computer Vision, Princeton, New Jersey, Oct. 1998, pp. 15-21.
[27] J. W. Hsieh, C. H. Chuang, S. Y. Chen, C. C. Chen, and K. C. Fan, “Segmentation of human body parts using deformable triangulation,” IEEE Transactions on Systems Man and Cybernetics Part a-Systems and Humans, vol. 40, no. 3, pp. 596-610, 2010.
[28] C. C. Chen, J. W. Hsieh, Y. T. Hsu, and C. Y. Huang, “Segmentation of human body parts using deformable triangulation,” in International Conference on Pattern Recognition (ICPR′06), Hong Kong, Aug. 2006, pp. 355-358.
[29] C. H. Chuang, J. W. Hsieh, L. W. Tsai, and K. C. Fan, “Human action recognition using star templates and delaunay triangulation,” in International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Harbin, China, Aug. 2008. pp. 179-182.
[30] J. W. Hsieh, Y. T. Hsu, H. Y. M. Liao, and C. C. Chen, “Video-based human movement analysis and its application to surveillance systems,” IEEE Transactions on Multimedia, vol. 10, no. 3, pp. 372-384, 2008.
[31] C. F. Juang, C. M. Chang, J. R. Wu, and D. M. Lee, “Computer vision-based human body segmentation and posture estimation,” IEEE Transactions on Systems Man and Cybernetics Part a-Systems and Humans, vol. 39, no. 1, pp. 119-133, 2009.
[32] D. T. Chen, H. Y. M. Liao, H. R. Tyan, and C. W. Lin, “Automatic key posture selection for human behavior analysis,” in IEEE Workshop on Multimedia Signal Processing, Shanghai, China, Oct. 2005, pp. 1-4.
[33] S. Chen, P. Akselrod, B. Zhao, J. A. P. Carrasco, B. Linares-Barranco, and E. Culurciello, “Efficient feedforward categorization of objects and human postures with address-event image sensors,” IEEE Trans Pattern Anal Mach Intell, vol. 34, no. 2, pp. 302-314, 2012.
[34] C. F. Juang, and C. M. Chang, “Human body posture classification by a neural fuzzy network and home care system application,” IEEE Transactions on Systems Man and Cybernetics Part a-Systems and Humans, vol. 37, no. 6, pp. 984-994, 2007.
[35] G. Diraco, A. Leone, and P. Siciliano, “Human posture recognition with a time-of-flight 3D sensor for in-home applications,” Expert Systems with Applications, vol. 40, no. 2, pp. 744-751, 2013.
[36] D. Brulin, Y. Benezeth, and E. Courtial, “Posture recognition based on fuzzy logic for home monitoring of the elderly,” IEEE Transactions on Information Technology in Biomedicine, vol. 16, no. 5, pp. 974-982, 2012.
[37] L. Xia, C. C. Chen, and J. K. Aggarwal, “View invariant human action recognition using histograms of 3D joints,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, Providence, RI, Jun. 2012, pp. 20-27.
[38] T. L. Le, M. Q. Nguyen, and T. T. M. Nguyen, “Human posture recognition using human skeleton provided by Kinect,” in International Conference on Computing, Management and Telecommunications (ComManTel), Ho Chi Minh, Vietnam, Jan. 2013, pp. 340-345.
[39] I. Patsadu, C. Nukoolkit, and B. Watanapa, “Human gesture recognition using Kinect camera. In International Joint Conference on Computer Science and Software Engineering (JCSSE), Bangkok, Thailand, May 2012, pp. 28-32.
[40] B. J. Southwell and G. Fang, “Human object recognition using colour and depth information from an RGB-D Kinect sensor,” International Journal of Advanced Robotic Systems, vol. 10, 2013.
[41] C. Granata, A. Ibanez, and P. Bidaud, “Human activity-understanding: a multilayer approach combining body movements and contextual descriptors analysis,” International Journal of Advanced Robotic Systems, vol. 12, 2015.
[42] Z. Zhang, Y. Liu, A. Li, and M. Wang, “A novel method for user-defined human posture recognition using Kinect,” in International Congress on Image and Signal Processing (CISP), Dalian, China, Oct. 2014, pp. 736-740.
[43] D. Catuhe, Programming with the Kinect for windows software development kit redmond. 1st ed. Microsoft Press; 2012.
[44] M. T. Pilevar, H. Feili, and M. Soltani, “Classification of persian textual documents using Learning Vector Quantization,” in national Conference on Natural Language Processing and Knowledge Engineering, Dalian, China, Sep. 2009, pp. 1-6.
[45] H. Xiao, L. Yu, and K. Chen, “An efficient method of language identification using LVQ Network,” in International Conference on Signal Processing, Beijing, China, Oct. 2008, pp. 1690-1694.
[46] C. Wang, H. Zhang, and C. Yu, “Research on color recognition of urine test paper based on learning vector quantization (LVQ),” in International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC), Harbin, China, Dec. 2012, pp. 850-853.
[47] Kinect for windows, https://developer.microsoft.com/en-us/windows/kinect/
[48] J. Aleotti and S. Caselli, “Interactive teaching of task-oriented robot grasps,” Robotics and Autonomous Systems, vol. 58, no. 5, pp. 539-550, 2010.
[49] S. R. Munasinghe, M. Nakamura, S. Goto, and N. Kyura, “Optimum contouring of industrial robot arms under assigned velocity and torque constraints,” IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications And Reviews, vol. 31, no. 2, pp. 159-167, 2001.
[50] C. W. Kennedy and J. P. Desai, “Modeling and control of the Mitsubishi PA-10 robot arm harmonic drive system,” IEEE-ASME Transactions on Mechatronics, vol. 10, no. 3, pp. 263-274, 2005.
[51] W. Shen, J. Gu, and E. E. Milios, “Self-configuration fuzzy system for inverse kinematics of robot manipulators,” in Annual Meeting of the North American Fuzzy Information Processing Society, Montreal, QC, Canada, Jun. 2006, pp. 41-45.
[52] V. Feliu, J. A. Somolinos, and A. Garcia, “Inverse dynamics based control system for a three-degree-of-freedom flexible arm,” IEEE Transactions on Robotics and Automation, vol. 19, no. 6, pp. 1007-1014, 2003.
[53] M. Shimizu, H. Kakuya, W. K. Yoon, K. Kitagaki, and K. Kosuge, “Analytical inverse kinematic computation for 7-DOF redundant manipulators with joint limits and its application to redundancy resolution,” IEEE Transactions on Robotics, vol. 24, no. 5, pp. 1131-1142, 2008.
[54] W. J. Wang, C. H. Huang, I. H. Lai, and H. C. Chen, “A robot arm for pushing elevator buttons,” in Proceedings of SICE Annual Conference, Taipei, Taiwan, Aug. 2010, pp. 1844-1848.
[55] A. Nilsson and P. Holmberg, “Combining a stable 2-D vision camera and an ultrasonic range detector for 3-D position estimation,” IEEE Transactions on Instrumentation and Measurement, vol. 43, no. 2, pp. 272-276, 1994.
[56] J. Y. Baek and M. C. Lee, “A study on detecting elevator entrance door using stereo vision in multi floor environment,” in ICROS-SICE International Joint Conference, Fukuoka, Japan, Aug. 2009, pp. 1370-1373.
[57] C. S. Fraser and S. Cronk, “A hybrid measurement approach for close-range photogrammetry,” Isprs Journal of Photogrammetry and Remote Sensing, vol. 64, no. 3, pp. 328-333, 2009.
[58] F. A. van den Heuvel, “3D reconstruction from a single image using geometric constraints,” Isprs Journal of Photogrammetry and Remote Sensing, vol. 53, no. 6, pp. 354-368, 1998.
[59] D. H. Zhang, J. Liang, and C. Guo, “Photogrammetric 3D measurement method applying to automobile panel,” in International Conference on Computer and Automation Engineering (ICCAE), Singapore, Feb. 2010, pp. 70-74.
[60] T. Egami, S. Oe, K. Terada, and T. Kashiwagi, “Three dimensional measurement using color image and movable CCD system,” in Annual Conference of the IEEE Industrial Electronics Society, Denver, Colorado, USA, Nov. 2001, pp. 1932-1936.
[61] C. C. Hsu, M. C. Lu, W. Y. Wang, and Y. Y. Lu, “Three-dimensional measurement of distant objects based on laser-projected CCD images,” IET Science Measurement & Technology, vol. 3, no. 3, pp. 197-207, 2009.
[62] J. J. Aguilar, F. Torres, and M. A. Lope, “Stereo vision for 3D measurement: accuracy analysis, calibration and industrial applications,” Measurement, vol. 18, no. 4, pp. 193-200, 1996.
[63] L. Feng, L. Xiaoyu, and C. Yi, “An efficient detection method for rare colored capsule based on RGB and HSV color space.” In IEEE International Conference on Granular Computing (GrC), Noboribetsu, Japan, Oct. 2014, pp. 175-175.
[64] R. Laganie`re, OpenCV2 computer vision application programming Cookbook, Birmingham: Packt Publishing, 2011.
[65] R. Jain, R. Kasturi, and B. G. Schunk, Machine Vision. New York: McGraw-Hill, 1995.
[66] B. S. Kim, S. H. Lee, and N. I. Cho, “Real-time panorama canvas of natural images,” IEEE Transactions on Consumer Electronics, vol. 57, no. 4, pp. 1961-1968, 2011.
[67] M. Bellone, G. Reina, N. I. Giannoccaro, and L. Spedicato, “Unevenness point descriptor for terrain analysis in mobile robot applications,” International Journal of Advanced Robotic Systems, vol. 10, 2013.
[68] S. Laible, Y. N. Khan, and A. Zell, “Terrain classification with conditional random fields on fused 3D LIDAR and camera data,” European Conference on Mobile Robots (ECMR), Barcelona, Spain, Set. 2013, pp. 172-177.
[69] G. Jia, X. Wang, and H. Wei, “An effective approach for selection of terrain modeling methods,” IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 4, pp. 875-879, 2013.
[70] G. Reina, A. Milella, and J. Underwood, “Self-learning classification of radar features for scene understanding,” Robotics and Autonomous Systems, vol. 60, no. 11, pp. 1377-1388, 2012.
[71] F. L. G. Bermudez, R. C. Julian, D. W. Haldane, P. Abbeel, and R. S. Fearing, “Performance analysis and terrain classification for a legged robot over rough terrain,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Algarve, Portugal, Oct. 2012, pp. 513-519.
[72] D. Tick, T. Rahman, C. Busso, and N. Gans, “Indoor robotic terrain classification via angular velocity based hierarchical classifier selection,” in IEEE International Conference on Robotics and Automation (ICRA), Saint Paul, Minnesota, May 2012, pp. 3594-3600.
[73] M. Häselich, M. Arends, N. Wojke, F. Neuhaus, and D. Paulus, “Probabilistic terrain classification in unstructured environments,” Robotics and Autonomous Systems, vol. 61, no. 10, pp. 1051-1059, 2013.
[74] K. Walas, “Terrain classification and negotiation with a walking robot,” Journal of Intelligent & Robotic Systems, vol. 78, pp. 401-423, 2015.
[75] J. Jiang, D. Tu, S. Xu, and Q. Zhao, “Cognitive response navigation algorithm for mobile robots using biological antennas,” Robotica, vol. 32, no. 5, pp. 743-756, 2014.
[76] X. Yang, M. Moallem, and R. V. Patel, “A layered goal-oriented fuzzy motion planning strategy for mobile robot navigation,” IEEE Transactions on Systems, Man, and Cybernetics, Part B Cybernetics, vol. 35, no. 6, pp. 1214-1224, 2005.
[77] C. Ye and P. Webb, “A sub goal seeking approach for reactive navigation in complex unknown environments,” Robotics and Autonomous Systems, vol. 57, no. 9, pp. 877-888, 2009.
[78] O. R. E. Motlagh, T. S. Hong, and N. Ismail, “Development of a new minimum avoidance system for a behavior-based mobile robot,” Fuzzy Sets and Systems, vol. 160, no. 13, pp. 1929-1946, 2009.
[79] M. F. R. Lee, F. H. S. Chiu, C. W. de Silva, and C. Y. A. Shih, “Intelligent navigation and micro-spectrometer content inspection system for a homecare mobile robot,” International Journal of Fuzzy Systems, vol. 16, no. 3, pp. 389-399, 2014.
[80] XtionPro, https://www.asus.com/3D-Sensor/Xtion_PRO/
[81] A robot moves from lower level to higher level, https://youtu.be/NA3seYi9k0E
[82] A robot moves from higher level to lower level, https://youtu.be/MigPSI6wWPQ |