{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T22:05:06Z","timestamp":1782597906151,"version":"3.54.5"},"reference-count":41,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2023,8,23]],"date-time":"2023-08-23T00:00:00Z","timestamp":1692748800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005416","name":"Norges Forskningsr\u00e5d","doi-asserted-by":"publisher","award":["280835"],"award-info":[{"award-number":["280835"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005416","name":"Norges Forskningsr\u00e5d","doi-asserted-by":"publisher","award":["287918"],"award-info":[{"award-number":["287918"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Applied Soft Computing"],"published-print":{"date-parts":[[2023,11]]},"DOI":"10.1016\/j.asoc.2023.110773","type":"journal-article","created":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T20:54:13Z","timestamp":1693428853000},"page":"110773","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":89,"special_numbering":"C","title":["Q-learning-based unmanned aerial vehicle path planning with dynamic obstacle avoidance"],"prefix":"10.1016","volume":"147","author":[{"given":"Amala","family":"Sonny","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sreenivasa Reddy","family":"Yeduri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1023-2118","authenticated-orcid":false,"given":"Linga Reddy","family":"Cenkeramaddi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.asoc.2023.110773_b1","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.neucom.2022.05.006","article-title":"A deep reinforcement learning based method for real-time path planning and dynamic obstacle avoidance","volume":"497","author":"Chen","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.asoc.2023.110773_b2","doi-asserted-by":"crossref","unstructured":"L. Yang, J. Qi, J. Xiao, X. Yong, A literature review of UAV 3D path planning, in: Proceeding of the 11th World Congress on Intelligent Control and Automation, 2014, pp. 2376\u20132381, http:\/\/dx.doi.org\/10.1109\/WCICA.2014.7053093.","DOI":"10.1109\/WCICA.2014.7053093"},{"key":"10.1016\/j.asoc.2023.110773_b3","doi-asserted-by":"crossref","unstructured":"F. Borrelli, D. Subramanian, A. Raghunathan, L. Biegler, MILP and NLP Techniques for centralized trajectory planning of multiple unmanned air vehicles, in: 2006 American Control Conference, 2006, p. 6, http:\/\/dx.doi.org\/10.1109\/ACC.2006.1657644.","DOI":"10.1109\/ACC.2006.1657644"},{"key":"10.1016\/j.asoc.2023.110773_b4","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2020.105046","article-title":"A dynamic path planning approach for dense, large, grid-based automated guided vehicle systems","volume":"123","author":"Fransen","year":"2020","journal-title":"Comput. Oper. Res."},{"key":"10.1016\/j.asoc.2023.110773_b5","doi-asserted-by":"crossref","unstructured":"M. Kanehara, S. Kagami, J.J. Kuffner, S. Thompson, H. Mizoguhi, Path shortening and smoothing of grid-based path planning with consideration of obstacles, in: 2007 IEEE International Conference on Systems, Man and Cybernetics, 2007, pp. 991\u2013996, http:\/\/dx.doi.org\/10.1109\/ICSMC.2007.4414077.","DOI":"10.1109\/ICSMC.2007.4414077"},{"key":"10.1016\/j.asoc.2023.110773_b6","doi-asserted-by":"crossref","unstructured":"J. Barraquand, B. Langlois, J.-C. Latombe, Numerical potential field techniques for robot path planning, in: Fifth International Conference on Advanced Robotics \u2019Robots in Unstructured Environments, 1991, pp. 1012\u20131017 vol.2, http:\/\/dx.doi.org\/10.1109\/ICAR.1991.240539.","DOI":"10.1109\/ICAR.1991.240539"},{"key":"10.1016\/j.asoc.2023.110773_b7","doi-asserted-by":"crossref","unstructured":"F. Bounini, D. Gingras, H. Pollart, D. Gruyer, Modified artificial potential field method for online path planning applications, in: 2017 IEEE Intelligent Vehicles Symposium (IV), 2017, pp. 180\u2013185, http:\/\/dx.doi.org\/10.1109\/IVS.2017.7995717.","DOI":"10.1109\/IVS.2017.7995717"},{"issue":"2","key":"10.1016\/j.asoc.2023.110773_b8","doi-asserted-by":"crossref","first-page":"1500","DOI":"10.1109\/LRA.2020.2969191","article-title":"An efficient sampling-based method for online informative path planning in unknown environments","volume":"5","author":"Schmid","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"issue":"4","key":"10.1016\/j.asoc.2023.110773_b9","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1109\/TRO.2010.2049527","article-title":"Sampling-based path planning on configuration-space costmaps","volume":"26","author":"Jaillet","year":"2010","journal-title":"IEEE Trans. Robot."},{"issue":"2","key":"10.1016\/j.asoc.2023.110773_b10","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1109\/TVT.2016.2555853","article-title":"Path planning and tracking for vehicle collision avoidance based on model predictive control with multiconstraints","volume":"66","author":"Ji","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"10.1016\/j.asoc.2023.110773_b11","doi-asserted-by":"crossref","unstructured":"C. Liu, S. Lee, S. Varnhagen, H.E. Tseng, Path planning for autonomous vehicles using model predictive control, in: 2017 IEEE Intelligent Vehicles Symposium (IV), 2017, pp. 174\u2013179, http:\/\/dx.doi.org\/10.1109\/IVS.2017.7995716.","DOI":"10.1109\/IVS.2017.7995716"},{"issue":"12","key":"10.1016\/j.asoc.2023.110773_b12","doi-asserted-by":"crossref","first-page":"9585","DOI":"10.1109\/TVT.2016.2623666","article-title":"A hybrid path planning method in unmanned air\/ground vehicle (UAV\/UGV) cooperative systems","volume":"65","author":"Li","year":"2016","journal-title":"IEEE Trans. Veh. Technol."},{"key":"10.1016\/j.asoc.2023.110773_b13","doi-asserted-by":"crossref","unstructured":"F.H. Tseng, T.T. Liang, C.H. Lee, L.D. Chou, H.C. Chao, A Star Search Algorithm for Civil UAV Path Planning with 3G Communication, in: 2014 Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2014, pp. 942\u2013945, http:\/\/dx.doi.org\/10.1109\/IIH-MSP.2014.236.","DOI":"10.1109\/IIH-MSP.2014.236"},{"key":"10.1016\/j.asoc.2023.110773_b14","doi-asserted-by":"crossref","unstructured":"Z. He, L. Zhao, The Comparison of Four UAV Path Planning Algorithms Based on Geometry Search Algorithm, in: 2017 9th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), Vol. 2, 2017, pp. 33\u201336, http:\/\/dx.doi.org\/10.1109\/IHMSC.2017.123.","DOI":"10.1109\/IHMSC.2017.123"},{"issue":"3","key":"10.1016\/j.asoc.2023.110773_b15","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1016\/j.asoc.2011.11.011","article-title":"Fuzzy dijkstra algorithm for shortest path problem under uncertain environment","volume":"12","author":"Deng","year":"2012","journal-title":"Appl. Soft Comput."},{"issue":"2","key":"10.1016\/j.asoc.2023.110773_b16","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1109\/JAS.2021.1004252","article-title":"An adaptive rapidly-exploring random tree","volume":"9","author":"Li","year":"2022","journal-title":"IEEE\/CAA J. Autom. Sin."},{"issue":"4","key":"10.1016\/j.asoc.2023.110773_b17","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1109\/70.508439","article-title":"Probabilistic roadmaps for path planning in high-dimensional configuration spaces","volume":"12","author":"Kavraki","year":"1996","journal-title":"IEEE Trans. Robot. Autom."},{"key":"10.1016\/j.asoc.2023.110773_b18","doi-asserted-by":"crossref","first-page":"157","DOI":"10.28991\/esj-2021-SPER-13","article-title":"Pid-based with odometry for trajectory tracking control on four-wheel omnidirectional covid-19 aromatherapy robot","volume":"5","author":"Ma\u2019arif","year":"2021","journal-title":"Emerg. Sci. J."},{"key":"10.1016\/j.asoc.2023.110773_b19","doi-asserted-by":"crossref","first-page":"241","DOI":"10.28991\/esj-2021-SP1-016","article-title":"Using a combination of PID control and Kalman filter to design of IoT-based telepresence self-balancing robots during COVID-19 pandemic","volume":"4","author":"Suwarno","year":"2020","journal-title":"Emerg. Sci. J."},{"key":"10.1016\/j.asoc.2023.110773_b20","first-page":"1","article-title":"Autonomous UAV path planning using modified PSO for UAV-assisted wireless networks","author":"Sonny","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.asoc.2023.110773_b21","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1016\/j.comcom.2019.10.014","article-title":"Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges","volume":"149","author":"Aggarwal","year":"2020","journal-title":"Comput. Commun."},{"key":"10.1016\/j.asoc.2023.110773_b22","doi-asserted-by":"crossref","unstructured":"S.I.A. Meerza, M. Islam, M.M. Uzzal, Q-Learning Based Particle Swarm Optimization Algorithm for Optimal Path Planning of Swarm of Mobile Robots, in: 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT), 2019, pp. 1\u20135, http:\/\/dx.doi.org\/10.1109\/ICASERT.2019.8934450.","DOI":"10.1109\/ICASERT.2019.8934450"},{"key":"10.1016\/j.asoc.2023.110773_b23","doi-asserted-by":"crossref","unstructured":"K.B. de\u00a0Carvalho, I.R.L. de\u00a0Oliveira, D.K.D. Villa, A.G. Caldeira, M. Sarcinelli-Filho, A.S. Brand\u00e3o, Q-learning based Path Planning Method for UAVs using Priority Shifting, in: 2022 International Conference on Unmanned Aircraft Systems (ICUAS), 2022, pp. 421\u2013426, http:\/\/dx.doi.org\/10.1109\/ICUAS54217.2022.9836175.","DOI":"10.1109\/ICUAS54217.2022.9836175"},{"issue":"5","key":"10.1016\/j.asoc.2023.110773_b24","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1109\/TSMCA.2012.2227719","article-title":"A deterministic improved Q-learning for path planning of a mobile robot","volume":"43","author":"Konar","year":"2013","journal-title":"IEEE Trans. Syst. Man Cybern.: Syst."},{"key":"10.1016\/j.asoc.2023.110773_b25","doi-asserted-by":"crossref","unstructured":"C. Yan, X. Xiang, A Path Planning Algorithm for UAV Based on Improved Q-Learning, in: 2018 2nd International Conference on Robotics and Automation Sciences (ICRAS), 2018, pp. 1\u20135, http:\/\/dx.doi.org\/10.1109\/ICRAS.2018.8443226.","DOI":"10.1109\/ICRAS.2018.8443226"},{"key":"10.1016\/j.asoc.2023.110773_b26","doi-asserted-by":"crossref","first-page":"7664","DOI":"10.1109\/ACCESS.2021.3139534","article-title":"Quality-oriented hybrid path planning based on A* and Q-learning for unmanned aerial vehicle","volume":"10","author":"Li","year":"2022","journal-title":"IEEE Access"},{"key":"10.1016\/j.asoc.2023.110773_b27","doi-asserted-by":"crossref","unstructured":"Z. Yijing, Z. Zheng, Z. Xiaoyi, L. Yang, Q learning algorithm based UAV path learning and obstacle avoidence approach, in: 2017 36th Chinese Control Conference (CCC), 2017, pp. 3397\u20133402, http:\/\/dx.doi.org\/10.23919\/ChiCC.2017.8027884.","DOI":"10.23919\/ChiCC.2017.8027884"},{"issue":"11","key":"10.1016\/j.asoc.2023.110773_b28","doi-asserted-by":"crossref","first-page":"2169","DOI":"10.3390\/app8112169","article-title":"UAV motion strategies in uncertain dynamic environments: A path planning method based on Q-learning strategy","volume":"8","author":"Cui","year":"2018","journal-title":"Appl. Sci."},{"key":"10.1016\/j.asoc.2023.110773_b29","doi-asserted-by":"crossref","unstructured":"Y. Gao, Y. Li, Z. Guo, A Q-learning based UAV Path Planning Method with Awareness of Risk Avoidance, in: 2021 China Automation Congress (CAC), 2021, pp. 669\u2013673, http:\/\/dx.doi.org\/10.1109\/CAC53003.2021.9728342.","DOI":"10.1109\/CAC53003.2021.9728342"},{"key":"10.1016\/j.asoc.2023.110773_b30","first-page":"331","article-title":"Markov decision processes","volume":"2","author":"Puterman","year":"1990","journal-title":"Handb. Oper. Res. Manag. Sci."},{"key":"10.1016\/j.asoc.2023.110773_b31","series-title":"Advances in Neural Information Processing Systems, Vol. 8","article-title":"Generalization in reinforcement learning: Successful examples using sparse coarse coding","author":"Sutton","year":"1995"},{"key":"10.1016\/j.asoc.2023.110773_b32","series-title":"Exact and Approximate Algorithms for Partially Observable Markov Decision Processes","author":"Cassandra","year":"1998"},{"issue":"1","key":"10.1016\/j.asoc.2023.110773_b33","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/S1389-0417(01)00015-8","article-title":"Value-function reinforcement learning in Markov games","volume":"2","author":"Littman","year":"2001","journal-title":"Cogn. Syst. Res."},{"key":"10.1016\/j.asoc.2023.110773_b34","series-title":"Advances in Neural Information Processing Systems, Vol. 12","article-title":"Policy gradient methods for reinforcement learning with function approximation","author":"Sutton","year":"1999"},{"key":"10.1016\/j.asoc.2023.110773_b35","doi-asserted-by":"crossref","unstructured":"C. Ye, J. Borenstein, A method for mobile robot navigation on rough terrain, in: IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA \u201904. 2004, Vol. 4, 2004, pp. 3863\u20133869, http:\/\/dx.doi.org\/10.1109\/ROBOT.2004.1308870, Vol.4.","DOI":"10.1109\/ROBOT.2004.1308870"},{"key":"10.1016\/j.asoc.2023.110773_b36","doi-asserted-by":"crossref","first-page":"92879","DOI":"10.1109\/ACCESS.2022.3203072","article-title":"Improved Q-learning applied to dynamic obstacle avoidance and path planning","volume":"10","author":"Wang","year":"2022","journal-title":"IEEE Access"},{"issue":"3","key":"10.1016\/j.asoc.2023.110773_b37","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1080\/09528130903157377","article-title":"Reinforcement learning via approximation of the Q-function","volume":"22","author":"Langlois","year":"2010","journal-title":"J. Exp. Theor. Artif. Intell."},{"issue":"1\u20134","key":"10.1016\/j.asoc.2023.110773_b38","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1007\/s10846-011-9619-8","article-title":"Path planning for UAVs under communication constraints using SPLAT! and MILP","volume":"65","author":"Gr\u00f8tli","year":"2012","journal-title":"J. Intell. Robot. Syst."},{"key":"10.1016\/j.asoc.2023.110773_b39","doi-asserted-by":"crossref","first-page":"59196","DOI":"10.1109\/ACCESS.2021.3070054","article-title":"Geometric A-star algorithm: An improved A-star algorithm for AGV path planning in a port environment","volume":"9","author":"Tang","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.asoc.2023.110773_b40","doi-asserted-by":"crossref","first-page":"147827","DOI":"10.1109\/ACCESS.2020.3015976","article-title":"Surface optimal path planning using an extended dijkstra algorithm","volume":"8","author":"Luo","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.asoc.2023.110773_b41","doi-asserted-by":"crossref","unstructured":"H. Boming, L. Wei, M. Fuzeng, F. Huahao, Research for UAV Path Planning Method Based on Guided Sarsa Algorithm, in: 2022 IEEE 2nd International Conference on Software Engineering and Artificial Intelligence (SEAI), 2022, pp. 220\u2013224, http:\/\/dx.doi.org\/10.1109\/SEAI55746.2022.9832224.","DOI":"10.1109\/SEAI55746.2022.9832224"}],"container-title":["Applied Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494623007913?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494623007913?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:25:48Z","timestamp":1761596748000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1568494623007913"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11]]},"references-count":41,"alternative-id":["S1568494623007913"],"URL":"https:\/\/doi.org\/10.1016\/j.asoc.2023.110773","relation":{},"ISSN":["1568-4946"],"issn-type":[{"value":"1568-4946","type":"print"}],"subject":[],"published":{"date-parts":[[2023,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Q-learning-based unmanned aerial vehicle path planning with dynamic obstacle avoidance","name":"articletitle","label":"Article Title"},{"value":"Applied Soft Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.asoc.2023.110773","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"110773"}}