Literatura académica sobre el tema "Autonomous search"
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Artículos de revistas sobre el tema "Autonomous search"
Gelenbe, Erol y Yonghuan Cao. "Autonomous search for mines". European Journal of Operational Research 108, n.º 2 (julio de 1998): 319–33. http://dx.doi.org/10.1016/s0377-2217(97)00373-1.
Texto completoHuo, Jianwen, Manlu Liu, Konstantin A. Neusypin, Haojie Liu, Mingming Guo y Yufeng Xiao. "Autonomous Search of Radioactive Sources through Mobile Robots". Sensors 20, n.º 12 (19 de junio de 2020): 3461. http://dx.doi.org/10.3390/s20123461.
Texto completoMansor, Hasmah, Muhamad Haziq Norhisam, Zulkifli Zainal Abidin y Teddy Surya Gunawan. "Autonomous surface vessel for search and rescue operation". Bulletin of Electrical Engineering and Informatics 10, n.º 3 (1 de junio de 2021): 1701–8. http://dx.doi.org/10.11591/eei.v10i3.2599.
Texto completoHarel, David, Assaf Marron y Joseph Sifakis. "Autonomics: In search of a foundation for next-generation autonomous systems". Proceedings of the National Academy of Sciences 117, n.º 30 (21 de julio de 2020): 17491–98. http://dx.doi.org/10.1073/pnas.2003162117.
Texto completoSYAFITRI, NIKEN, RATNA SUSANA, IHSAN FARRASSALAM AMMARPRAWIRA, MOCHAMAD SEPTONI FAUZI y ARBI ABDUL JABBAAR. "The Autonomous Disaster Victim Search Robot using the Waypoint Method". ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 8, n.º 2 (19 de mayo de 2020): 347. http://dx.doi.org/10.26760/elkomika.v8i2.347.
Texto completoPiacentini, Chiara, Sara Bernardini y J. Christopher Beck. "Autonomous Target Search with Multiple Coordinated UAVs". Journal of Artificial Intelligence Research 65 (8 de agosto de 2019): 519–68. http://dx.doi.org/10.1613/jair.1.11635.
Texto completoDollarhide, Robert L., Arvin Agah y Gary J. Minden. "Evolving controllers for autonomous robot search teams". Artificial Life and Robotics 5, n.º 3 (septiembre de 2001): 178–88. http://dx.doi.org/10.1007/bf02481466.
Texto completoSoto, Ricardo, Broderick Crawford, Wenceslao Palma, Karin Galleguillos, Carlos Castro, Eric Monfroy, Franklin Johnson y Fernando Paredes. "Boosting autonomous search for CSPs via skylines". Information Sciences 308 (julio de 2015): 38–48. http://dx.doi.org/10.1016/j.ins.2015.01.035.
Texto completode Cubber, Geert, Haris Balta y Claude Lietart. "Teodor: A Semi-Autonomous Search and Rescue and Demining Robot". Applied Mechanics and Materials 658 (octubre de 2014): 599–605. http://dx.doi.org/10.4028/www.scientific.net/amm.658.599.
Texto completoLiu, Yuan, Min Wang, Zhou Su, Jun Luo, Shaorong Xie, Yan Peng, Huayan Pu, Jiajia Xie y Rui Zhou. "Multi-AUVs Cooperative Target Search Based on Autonomous Cooperative Search Learning Algorithm". Journal of Marine Science and Engineering 8, n.º 11 (26 de octubre de 2020): 843. http://dx.doi.org/10.3390/jmse8110843.
Texto completoTesis sobre el tema "Autonomous search"
Peterson, John Ryan. "Autonomous Source Localization". Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/97954.
Texto completoDoctor of Philosophy
This work discusses the use of unmanned aerial and ground vehicles to autonomously locate radioactive materials. Using radiation detectors onboard each vehicle, they are commanded to search the environment using a method that incorporates measurements as they are collected. A mathematical model allows measurements taken from different vehicles in different positions to be combined together. This approach decreases the time required to locate sources by using previously collected measurements to improve the quality of later measurements. This approach also provides a best estimate of the location of a source as data is collected. This algorithm was tested in an experiment conducted at Savannah River National Laboratory. Further numerical experiments were conducted testing different reward functions and exploration algorithms.
Cavallin, Kristoffer y Peter Svensson. "Semi-Autonomous,Teleoperated Search and Rescue Robot". Thesis, Umeå University, Department of Computing Science, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-31928.
Texto completoThe interest in robots in the urban search and rescue (USAR) field has increased the last two decades. The idea is to let robots move into places where human rescue workers cannot or, due to high personal risks, should not enter.In this thesis project, an application is constructed with the purpose of teleoperating a simple robot. This application contains a user interface that utilizes both autonomous and semi-autonomous functions, such as search, explore and point-and-go behaviours. The purpose of the application is to work with USAR principles in a refined and simplified environment, and thereby increase the understanding for these principles and how they interact with each other. Furthermore, the thesis project reviews the recent and the current status of robots in USAR applications and use of teleoperation and semi-autonomous robots in general. Some conclusions that are drawn towards the end of the thesis are that the use of robots, especially in USAR situations, will continue to increase. As robots and support technology both become more advanced and cheaper by the day, teleoperation and semi-autonomous robots will also be seen in more and more places.
Earnest, Caleb A. "Dynamic action spaces for autonomous search operations". Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/46549.
Texto completoIncludes bibliographical references (p. 148-150).
This thesis presents a new approach for a Navy unmanned undersea vehicle (UUV) to search for and detect an evading contact. This approach uses a contact position distribution from a generic particle filter to estimate the state of a single moving contact and to plan the path that minimizes the uncertainty in the location of the contact. The search algorithms introduced in this thesis will implement a motion planner that searches for a contact with the following information available to the decision system: (1) null measurement (i.e., contact not detected at current time), (2) timedated measurement (i.e., clue found at current time that indicates contact was at this location in the past), and (3) bearings measurement (i.e., angular measurement towards contact position detected at current time). The results of this thesis will be arrived at by evaluating the best methods to utilize the three types of information. The underlying distribution of the contact state space will be modeled using a generic particle filter, due to the highly non-Gaussian distributions that result from the conditions mentioned above. Using the particle filter distribution and the measurements acquired from the three conditions, this thesis will work towards implementing a path planning algorithm that creates dynamic action spaces that evaluate the uncertainty of position distribution. Ultimately, the path planner will choose the path that contains the position distribution and leads to sustained searches.
by Caleb A. Earnest.
S.M.
Beck, Zoltan. "Collaborative search and rescue by autonomous robots". Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/411031/.
Texto completoHammerseth, Vegard B. "Autonomous Unmanned Aerial Vehicle In Search And Rescue". Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for teknisk kybernetikk, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-22880.
Texto completoRyu, Kun Jin. "Autonomous Robotic Strategies for Urban Search and Rescue". Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/19194.
Texto completoefficiency of their cooperation each member of the team specifically works on its own task.
A series of numerical and experimental studies were conducted to demonstrate the applicability of the proposed solutions to USAR scenarios. The effectiveness of the scan-to-map matching with the multi-ND representation was confirmed by analyzing the error accumulation and by comparing with the single-ND representation. The applicability of the scan-to-map matching to the real SLAM problem was also verified in three different real environments. The results of the map-based semi-autonomous robot navigation showed the effectiveness of the approach as an immediately usable solution to USAR. The effectiveness of the proposed fully- autonomous solution was first confirmed by two real robots in a real environment. The cooperative performance of the strategy was further investigated using the developed platform- and hardware-in-the-loop simulator. The results showed significant potential as the future solution to USAR.
Ph. D.
Finegan, Edward Graham. "Intelligent Autonomous Data Categorization". VCU Scholars Compass, 2005. http://scholarscompass.vcu.edu/etd/1343.
Texto completoCompton, Mark A. "Minefield search and object recognition for autonomous underwater vehicles". Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/30604.
Texto completoAmbrose-Thurman, Andrew Michael Luke. "Autonomous, collaborative, unmanned aerial vehicles for search and rescue". Thesis, Durham University, 2014. http://etheses.dur.ac.uk/10652/.
Texto completoBeyme, Steffen. "Autonomous, wireless sensor network-assisted target search and mapping". Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/50725.
Texto completoApplied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
Libros sobre el tema "Autonomous search"
Hamadi, Youssef, Eric Monfroy y Frédéric Saubion. Autonomous search. Heidelberg: Springer, 2011.
Buscar texto completoEric, Monfroy, Saubion Frédéric y SpringerLink (Online service), eds. Autonomous Search. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Buscar texto completoHamadi, Youssef, Eric Monfroy y Frédéric Saubion, eds. Autonomous Search. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-21434-9.
Texto completoReal-time search for learning autonomous agents. Boston: Kluwer Academic Publishers, 1997.
Buscar texto completoWang, Yue y Islam I. Hussein. Search and Classification Using Multiple Autonomous Vehicles. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2957-8.
Texto completoBurian, Erik Alfred. Search methods for an autonomous underwater vehicle using scalar measurements. Springfield, Va: Available from National Technical Information Service, 1996.
Buscar texto completoWang, Yue. Search and Classification Using Multiple Autonomous Vehicles: Decision-Making and Sensor Management. 2a ed. London: Springer London, 2012.
Buscar texto completoThe search for the Panchen Lama. New York: W.W. Norton, 2000.
Buscar texto completoA mountain in Tibet: The search for Mount Kailas and the sources of the great rivers of India. London: Abacus, 2003.
Buscar texto completoForeign devils on the Silk Road: The search for the lost cities and treasures of Chinese Central Asia. Oxford: Oxford University Press, 2001.
Buscar texto completoCapítulos de libros sobre el tema "Autonomous search"
Petrik, Marek y Shlomo Zilberstein. "Learning Feature-Based Heuristic Functions". En Autonomous Search, 269–305. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_11.
Texto completoHamadi, Youssef, Eric Monfroy y Frédéric Saubion. "An Introduction to Autonomous Search". En Autonomous Search, 1–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_1.
Texto completoHamadi, Youssef, Said Jabbour y Jabbour Sais. "Control-Based Clause Sharing in Parallel SAT Solving". En Autonomous Search, 245–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_10.
Texto completoEiben, A. E. y S. K. Smit. "Evolutionary Algorithm Parameters and Methods to Tune Them". En Autonomous Search, 15–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_2.
Texto completoHoos, Holger H. "Automated Algorithm Configuration and Parameter Tuning". En Autonomous Search, 37–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_3.
Texto completoBridge, Derek, Eoin O’Mahony y Barry O’Sullivan. "Case-Based Reasoning for Autonomous Constraint Solving". En Autonomous Search, 73–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_4.
Texto completoEpstein, Susan L. y Smiljana Petrovic. "Learning a Mixture of Search Heuristics". En Autonomous Search, 97–127. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_5.
Texto completoBattiti, Roberto y Paolo Campigotto. "An Investigation of Reinforcement Learning for Reactive Search Optimization". En Autonomous Search, 131–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_6.
Texto completoMaturana, Jorge, Álvaro Fialho, Frédéric Saubion, Marc Schoenauer, Frédéric Lardeux y Michèle Sebag. "Adaptive Operator Selection and Management in Evolutionary Algorithms". En Autonomous Search, 161–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_7.
Texto completoStützle, Thomas, Manuel López-Ibáñez, Paola Pellegrini, Michael Maur, Marco Montes de Oca, Mauro Birattari y Marco Dorigo. "Parameter Adaptation in Ant Colony Optimization". En Autonomous Search, 191–215. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21434-9_8.
Texto completoActas de conferencias sobre el tema "Autonomous search"
Gelenbe, Erol y Yonghuan Cao. "Autonomous search for mines". En AeroSense '97, editado por Abinash C. Dubey y Robert L. Barnard. SPIE, 1997. http://dx.doi.org/10.1117/12.280898.
Texto completoStevens, Timothy y Timothy H. Chung. "Autonomous search and counter-targeting using Levy search models". En 2013 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2013. http://dx.doi.org/10.1109/icra.2013.6631134.
Texto completoNesterenko, P. A. y V. P. Gusev. "Autonomous anti-theft search satellite system". En 2014 12th International Conference on Actual Problems of Electronics Instrument Engineering (APEIE). IEEE, 2014. http://dx.doi.org/10.1109/apeie.2014.7040835.
Texto completoXue, Songdong, Jianchao Zeng y Guoyou Zhang. "A review of autonomous robotic search". En 2011 International Conference on Electrical and Control Engineering (ICECE). IEEE, 2011. http://dx.doi.org/10.1109/iceceng.2011.6057781.
Texto completoRasouli, Amir y John K. Tsotsos. "Visual Saliency Improves Autonomous Visual Search". En 2014 Canadian Conference on Computer and Robot Vision (CRV). IEEE, 2014. http://dx.doi.org/10.1109/crv.2014.23.
Texto completoCao, Yonghuan y Erol Gelenbe. "Autonomous search for mines: II. Hierarchical search using sensory data". En Aerospace/Defense Sensing and Controls, editado por Abinash C. Dubey, James F. Harvey y J. Thomas Broach. SPIE, 1998. http://dx.doi.org/10.1117/12.324143.
Texto completoPlenge, Benjamin y M. Anderson. "Wide area autonomous search munition search pattern "optimization" using genetic algorithms". En 39th Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2001. http://dx.doi.org/10.2514/6.2001-1124.
Texto completoBritt, Winard, William Lyles y David M. Bevly. "A State Machine Controller for the Autonomous Guidance of a Trained Canine". En ASME 2010 Dynamic Systems and Control Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/dscc2010-4020.
Texto completoPerera, Chamathke, Muhammad Galib y Ryan Tang Dan. "Autonomous Search and Rescue System (Project ASARS)". En The 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: “Industry, Innovation, and Infrastructure for Sustainable Cities and Communities”. Latin American and Caribbean Consortium of Engineering Institutions, 2019. http://dx.doi.org/10.18687/laccei2019.1.1.494.
Texto completoXu, Liheng, Chi Zhang, Yuehu Liu, Le Wang y Li Li. "Worst Perception Scenario Search for Autonomous Driving". En 2020 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2020. http://dx.doi.org/10.1109/iv47402.2020.9304731.
Texto completoInformes sobre el tema "Autonomous search"
Edwards, Dean B. Cooperative Autonomous Underwater Vehicles Used to Search Large Ocean Areas for Mines. Fort Belvoir, VA: Defense Technical Information Center, octubre de 2009. http://dx.doi.org/10.21236/ada507940.
Texto completoGage, Douglas W. Proceedings of the Autonomous Vehicles in Mine Countermeasures Symposium, Monterey CA, 4-7 April 1995 Many-Robot MCM Search Systems. Fort Belvoir, VA: Defense Technical Information Center, abril de 1995. http://dx.doi.org/10.21236/ada422749.
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