A Fully-Autonomous Aerial Robot for Search and Rescue Applications in Indoor Environments using Learning-Based Techniques
Tóm tắt
Từ khóa
Tài liệu tham khảo
Abrahamsen, H.B.: A remotely piloted aircraft system in major incident management: concept and pilot, feasibility study. BMC Emergency Medicine 15(1), 12 (2015)
Achtelik, M., Bachrach, A., He, R., Prentice, S., Roy, N.: Autonomous Navigation and Exploration of a Quadrotor Helicopter in Gps-Denied Indoor Environments. In: 1st Symposium on Indoor Flight, 2009. Citeseer (2009)
Bachrach, A., He, R., Roy, N.: Autonomous flight in unknown indoor environments. International Journal of Micro Air Vehicles 1(4), 217–228 (2009)
Bavle, H., Sanchez-Lopez, J.L., Rodriguez-Ramos, A., Sampedro, C., Campoy, P.: A Flight Altitude Estimator for Multirotor Uavs in Dynamic and Unstructured Indoor Environments. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), Pp. 1044–1051. https://doi.org/10.1109/ICUAS.2017.7991467 (2017)
Bejiga, M.B., Zeggada, A., Nouffidj, A., Melgani, F.: A convolutional neural network approach for assisting avalanche search and rescue operations with uav imagery. Remote Sens. 9(2), 100 (2017)
Brockman, G., Cheung, V., Pettersson, L., Schneider, J., Schulman, J., Tang, J., Zaremba, W.: Openai gym. arXiv: 1606.01540 (2016)
Carrio, A., Sampedro, C., Rodriguez-Ramos, A., Campoy, P.: A review of deep learning methods and applications for unmanned aerial vehicles. Journal of Sensors 2017 (2017)
Caruana, R., Niculescu-Mizil, A.: An empirical comparison of supervised learning algorithms. In: Proceedings of the 23rd international conference on Machine learning, pp. 161–168. ACM (2006)
Chang, C.C., Lin, C.J.: LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2, 27:1–27:27 (2011). Software available at http://www.csie.ntu.edu.tw/∼cjlin/libsvm
Chaumette, F.: Potential Problems of Stability and Convergence in Image-Based and Position-Based Visual Servoing. In: The Confluence of Vision and Control, pp. 66–78. Springer (1998)
Chaumette, F., Hutchinson, S.: Visual servo control. i. basic approaches. IEEE Robotics Automation Magazine 13(4), 82–90 (2006). https://doi.org/10.1109/MRA.2006.250573
Chaumette, F., Malis, E.: 2 1/2 D Visual Servoing: a Possible Solution to Improve Image-Based and Position-Based Visual Servoings. In: Proceedings of the IEEE International Conference on Robotics and Automation, 2000. ICRA’00, vol. 1, pp 630–635 (2000)
Dalal, N., Triggs, B.: Histograms of Oriented Gradients for Human Detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005. CVPR 2005, vol. 1, pp 886–893 (2005)
Doherty, P., Rudol, P.: A Uav Search and Rescue Scenario with Human Body Detection and Geolocalization. In: Australian Conference on Artificial Intelligence, vol. 4830, pp. 1–13. Springer (2007)
Dorigo, M., Colombetti, M.: Robot shaping: an experiment in behavior engineering. MIT press, Cambridge (1998)
Erdos, D., Erdos, A., Watkins, S.E.: An experimental uav system for search and rescue challenge. IEEE Aerosp. Electron. Syst. Mag. 28(5), 32–37 (2013)
Erez, T., Smart, W.D.: What Does Shaping Mean for Computational Reinforcement Learning? In: 7Th IEEE International Conference on Development and Learning, 2008. ICDL 2008, pp 215–219 (2008)
Fan, R.E., Chang, K.W., Hsieh, C.J., Wang, X.R., Lin, C.J.: LIBLINEAR: a library for large linear classification. J. Mach. Learn. Res. 9, 1871–1874 (2008)
Fleck, M.: Usability of lightweight defibrillators for uav delivery. In: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 3056–3061. ACM (2016)
Furrer, F., Burri, M., Achtelik, M., Siegwart, R.: Rotors-A Modular Gazebo Mav Simulator Framework. In: Robot Operating System (ROS), pp. 595–625. Springer (2016)
Gatteschi, V., Lamberti, F., Paravati, G., Sanna, A., Demartini, C., Lisanti, A., Venezia, G.: New Frontiers of Delivery Services Using Drones: a Prototype System Exploiting a Quadcopter for Autonomous Drug Shipments. In: 2015 IEEE 39Th Annual, Computer Software and Applications Conference (COMPSAC), vol. 2, pp. 920–927 (2015)
Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 580–587 (2014)
Grzonka, S., Grisetti, G., BUrgard, W.: A fully autonomous indoor quadrotor. IEEE Trans. Robot. 28 (1), 90–100 (2012)
Kingma, D., Ba, J.: Adam: A method for stochastic optimization arXiv: 1412.6980 (2014)
Kohlbrecher, S., Meyer, J., von Stryk, O., Klingauf, U.: A Flexible and Scalable Slam System with Full 3D Motion Estimation. In: Proceedings of the IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR) (2011)
Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet Classification with Deep Convolutional Neural Networks. In: Advances in Neural Information Processing Systems, pp. 1097–1105 (2012)
Laud, A.D.: Theory and application of reward shaping in reinforcement learning. Tech rep (2004)
Lee, A. X., Levine, S., Abbeel, P.: Learning visual servoing with deep features and fitted q-iteration arXiv: 1703.11000 (2017)
Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., Silver, D., Wierstra, D.: Continuous control with deep reinforcement learning arXiv: 1509.02971 (2015)
Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y., Berg, A.C.: Ssd:Single Shot Multibox Detector. In: European Conference on Computer Vision, pp. 21–37. Springer (2016)
Malis, E.: Improving Vision-Based Control Using Efficient Second-Order Minimization Techniques. In: Proceedings of the 2004 IEEE International Conference on Robotics and Automation, 2004. ICRA’04, vol. 2, pp 1843–1848 (2004)
Marchand, É., Spindler, F., Chaumette, F.: Visp for visual servoing: a generic software platform with a wide class of robot control skills. IEEE Robot. Autom. Mag. 12(4), 40–52 (2005)
Marder-Eppstein, E., Berger, E., Foote, T., Gerkey, B., Konolige, K.: The Office Marathon: Robust Navigation in an Indoor Office Environment. In: International Conference on Robotics and Automation (2010)
Meier, L., Tanskanen, P., Fraundorfer, F., Pollefeys, M.: Pixhawk: a System for Autonomous Flight Using Onboard Computer Vision. In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp 2992–2997 (2011)
Moore, T., Stouch, D.: A generalized extended kalman filter implementation for the robot operating system. In: Proceedings of the 13th International Conference on Intelligent Autonomous Systems (IAS-13). Springer (2014)
Nair, V., Hinton, G.E.: Rectified linear units improve restricted boltzmann machines. In: Proceedings of the 27th international conference on machine learning (ICML-10), pp. 807–814 (2010)
Pestana, J., Mellado-Bataller, I., Sanchez-Lopez, J.L., Fu, C., Mondragón, I.F., Campoy, P.: A general purpose configurable controller for indoors and outdoors gps-denied navigation for multirotor unmanned aerial vehicles. J. Intell. Robot. Syst. 73(1-4), 387–400 (2014)
Polvara, R., Patacchiola, M., Sharma, S., Wan, J., Manning, A., Sutton, R., Cangelosi, A.: Autonomous quadrotor landing using deep reinforcement learning arXiv: 1709.03339 (2017)
Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: Ros: an Open-Source Robot Operating System. In: ICRA Workshop on Open Source Software, vol. 3, pp. 5. Kobe, Japan (2009)
Ren, S., He, K., Girshick, R., Sun, J.: Faster R-Cnn: Towards Real-Time Object Detection with Region Proposal Networks. In: Advances in Neural Information Processing Systems, pp. 91–99 (2015)
Rudol, P., Doherty, P.: Human Body Detection and Geolocalization for Uav Search and Rescue Missions Using Color and Thermal Imagery. In: 2008 IEEE Aerospace Conference, pp. 1–8. IEEE (2008)
Sadeghi, F., Levine, S.: (cad)2rl: Real single-image flight without a single real image arXiv: 1611.04201 (2016)
Sampedro, C., Bavle, H., Rodríguez-Ramos, A., Carrio, A., Fernández, R.A.S., Sanchez-Lopez, J.L., Campoy, P.: A Fully-Autonomous Aerial Robotic Solution for the 2016 International Micro Air Vehicle Competition. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), pp 989–998. IEEE (2017)
Sampedro, C., Bavle, H., Sanchez-Lopez, J.L., Fernandez, R.A.S., Rodriguez-Ramos, A., Molina, M., Campoy, P.: A Flexible and Dynamic Mission Planning Architecture for Uav Swarm Coordination. In: 2016 International Conference on Unmanned Aircraft Systems (ICUAS), pp 355–363. IEEE (2016)
Sanchez-Lopez, J.L., Molina, M., Bavle, H., Sampedro, C., Fernández, R.A.S., Campoy, P.: A multi-layered component-based approach for the development of aerial robotic systems: The aerostack framework. J. Intell. Robot. Syst 88(2–4), 683–709 (2017)
Scherer, J., Yahyanejad, S., Hayat, S., Yanmaz, E., Andre, T., Khan, A., Vukadinovic, V., Bettstetter, C., Hellwagner, H., Rinner, B.: An autonomous multi-uav system for search and rescue. In: Proceedings of the First Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use, pp. 33–38. ACM (2015)
Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929–1958 (2014)
Sun, J., Li, B., Jiang, Y., Wen, C.Y.: A camera-based target detection and positioning uav system for search and rescue (sar) purposes. Sensors 16(11), 1778 (2016)
Tomic, T., Schmid, K., Lutz, P., Domel, A., Kassecker, M., Mair, E., Grixa, I.L., Ruess, F., Suppa, M., Burschka, D.: Toward a fully autonomous uav: Research platform for indoor and outdoor urban search and rescue. IEEE Robot. Autom. Mag. 19(3), 46–56 (2012)
Xiang, G., Hardy, A., Rajeh, M., Venuthurupalli, L.: Design of the Life-Ring Drone Delivery System for Rip Current Rescue. In: 2016 IEEE Systems and Information Engineering Design Symposium (SIEDS), pp 181–186. IEEE (2016)
Zhang, F., Leitner, J., Milford, M., Upcroft, B., Corke, P.: Towards vision-based deep reinforcement learning for robotic motion control arXiv: 1511.03791 (2015)
Zhu, Y., Mottaghi, R., Kolve, E., Lim, J.J., Gupta, A., Fei-Fei, L., Farhadi, A.: Target-Driven Visual Navigation in Indoor Scenes Using Deep Reinforcement Learning. In: 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 3357–3364 (2017)