參考文獻 |
參考文獻
1. Haraoka, T., S. Hayasaka, C. Murata, T. Yamaoka, and T. Ojima, Factors related to furniture anchoring: a method for reducing harm during earthquakes. Disaster medicine and public health preparedness, 2013. 7(1): p. 55-64.
2. Noji, E.K., Acute renal failure in natural disasters. Renal failure, 1992. 14(3): p. 245-249.
3. Balaguer, C., A. Gimenez, A. Jardon, R. Cabas, and R. Correal. Live experimentation of the service robot applications for elderly people care in home environments. in 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2005. IEEE.
4. Koselka, H., B. Wallach, and D. Gollaher, Autonomous personal service robot. 2007, Google Patents.
5. Reiser, U., C. Connette, J. Fischer, J. Kubacki, A. Bubeck, F. Weisshardt, T. Jacobs, C. Parlitz, M. Hägele, and A. Verl. Care-o-bot® 3-creating a product vision for service robot applications by integrating design and technology. in 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2009. IEEE.
6. Fang, Q., M. Kyrarini, D. Ristic-Durrant, and A. Gräser. RGB-D Camera based 3D Human Mouth Detection and Tracking Towards Robotic Feeding Assistance. in Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference. 2018.
7. Helm, V., S. Ercan, F. Gramazio, and M. Kohler. Mobile robotic fabrication on construction sites: DimRob. in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2012. IEEE.
8. Dörfler, K., T. Sandy, M. Giftthaler, F. Gramazio, M. Kohler, and J. Buchli, Mobile robotic brickwork, in Robotic Fabrication in Architecture, Art and Design 2016. 2016, Springer. p. 204-217.
9. Volkhardt, M., F. Schneemann, and H.-M. Gross. Fallen person detection for mobile robots using 3d depth data. in 2013 IEEE International Conference on Systems, Man, and Cybernetics. 2013. IEEE.
10. Antonello, M., M. Carraro, M. Pierobon, and E. Menegatti. Fast and robust detection of fallen people from a mobile robot. in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2017. IEEE.
11. Solbach, M.D. and J.K. Tsotsos. Vision-based fallen person detection for the elderly. in Proceedings of the IEEE International Conference on Computer Vision Workshops. 2017.
12. Iuga, C., P. Drăgan, and L. Bușoniu, Fall monitoring and detection for at-risk persons using a UAV. IFAC-PapersOnLine, 2018. 51(10): p. 199-204.
13. Ciabattoni, L., G. Foresi, A. Monteriu, D.P. Pagnotta, and L. Tomaiuolo. Fall detection system by using ambient intelligence and mobile robots. in 2018 Zooming Innovation in Consumer Technologies Conference (ZINC). 2018. IEEE.
14. Hess, W., D. Kohler, H. Rapp, and D. Andor. Real-time loop closure in 2D LIDAR SLAM. in 2016 IEEE International Conference on Robotics and Automation (ICRA). 2016. IEEE.
15. Pierzchała, M., P. Giguère, and R. Astrup, Mapping forests using an unmanned ground vehicle with 3D LiDAR and graph-SLAM. Computers and Electronics in Agriculture, 2018. 145: p. 217-225.
16. Zhou, X.S. and S.I. Roumeliotis. Multi-robot SLAM with unknown initial correspondence: The robot rendezvous case. in 2006 IEEE/RSJ international conference on intelligent robots and systems. 2006. IEEE.
17. Bhattacharya, S., R. Murrieta-Cid, and S. Hutchinson, Optimal paths for landmark-based navigation by differential-drive vehicles with field-of-view constraints. IEEE Transactions on Robotics, 2007. 23(1): p. 47-59.
18. Fox, D. KLD-sampling: Adaptive particle filters. in Advances in neural information processing systems. 2002.
19. Hennes, D., D. Claes, W. Meeussen, and K. Tuyls. Multi-robot collision avoidance with localization uncertainty. in AAMAS. 2012.
20. Duchoň, F., A. Babinec, M. Kajan, P. Beňo, M. Florek, T. Fico, and L. Jurišica, Path planning with modified a star algorithm for a mobile robot. Procedia Engineering, 2014. 96: p. 59-69.
21. Lee, D., G. Kim, D. Kim, H. Myung, and H.-T. Choi, Vision-based object detection and tracking for autonomous navigation of underwater robots. Ocean Engineering, 2012. 48: p. 59-68.
22. Benavidez, P. and M. Jamshidi. Mobile robot navigation and target tracking system. in 2011 6th International Conference on System of Systems Engineering. 2011. IEEE.
23. Jung, S., S. Hwang, H. Shin, and D.H. Shim, Perception, guidance, and navigation for indoor autonomous drone racing using deep learning. IEEE Robotics and Automation Letters, 2018. 3(3): p. 2539-2544.
24. Sweet, L.M. and M.C. Good. Re-definition of the robot motion control problem: Effects of plant dynamics, drive system constraints, and user requirements. in The 23rd IEEE conference on decision and control. 1984. IEEE.
25. Lumelsky, V.J. and E. Cheung, Real-time collision avoidance in teleoperated whole-sensitive robot arm manipulators. IEEE Transactions on Systems, Man, and Cybernetics, 1993. 23(1): p. 194-203.
26. Huang, C.-H., C.-S. Hsu, P.-C. Tsai, R.-J. Wang, and W.-J. Wang. Vision based 3-D position control for a robot arm. in 2011 IEEE International Conference on Systems, Man, and Cybernetics. 2011. IEEE.
27. Johns, E., S. Leutenegger, and A.J. Davison. Deep learning a grasp function for grasping under gripper pose uncertainty. in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2016. IEEE.
28. Hernandez, C., M. Bharatheesha, W. Ko, H. Gaiser, J. Tan, K. van Deurzen, M. de Vries, B. Van Mil, J. van Egmond, and R. Burger. Team delft’s robot winner of the amazon picking challenge 2016. in Robot World Cup. 2016. Springer.
29. Quigley, M., K. Conley, B. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, and A.Y. Ng. ROS: an open-source Robot Operating System. in ICRA workshop on open source software. 2009. Kobe, Japan.
30. Quigley, M., B. Gerkey, and W.D. Smart, Programming Robots with ROS: a practical introduction to the Robot Operating System. 2015: " O′Reilly Media, Inc.".
31. Ang, K.H., G. Chong, and Y. Li, PID control system analysis, design, and technology. IEEE transactions on control systems technology, 2005. 13(4): p. 559-576.
32. Mullane, J., B.-N. Vo, M.D. Adams, and W.S. Wijesoma. A random set formulation for Bayesian SLAM. in 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2008. IEEE.
33. Yao, J., C. Lin, X. Xie, A.J. Wang, and C.-C. Hung. Path planning for virtual human motion using improved A* star algorithm. in 2010 Seventh international conference on information technology: new generations. 2010. IEEE.
34. Ogren, P. and N.E. Leonard, A convergent dynamic window approach to obstacle avoidance. IEEE Transactions on Robotics, 2005. 21(2): p. 188-195.
35. Chitta, S., MoveIt!: an introduction, in Robot Operating System (ROS). 2016, Springer. p. 3-27.
36. Sucan, I.A., M. Moll, and L.E. Kavraki, The open motion planning library. IEEE Robotics & Automation Magazine, 2012. 19(4): p. 72-82.
37. Corke, P.I., A simple and systematic approach to assigning Denavit–Hartenberg parameters. IEEE transactions on robotics, 2007. 23(3): p. 590-594.
38. Goldenberg, A., B. Benhabib, and R. Fenton, A complete generalized solution to the inverse kinematics of robots. IEEE Journal on Robotics and Automation, 1985. 1(1): p. 14-20.
39. Howard, A.G., M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam, Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861, 2017.
40. Liu, W., D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A.C. Berg. Ssd: Single shot multibox detector. in European conference on computer vision. 2016. Springer. |