{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T01:19:54Z","timestamp":1774919994925,"version":"3.50.1"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T00:00:00Z","timestamp":1726185600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T00:00:00Z","timestamp":1726185600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Natural Science Foundation of Fujian Provincial Science and Technology Department","award":["No.2021H6037"],"award-info":[{"award-number":["No.2021H6037"]}]},{"DOI":"10.13039\/501100018623","name":"Quanzhou Science and Technology Project","doi-asserted-by":"crossref","award":["No.2021C0008R"],"award-info":[{"award-number":["No.2021C0008R"]}],"id":[{"id":"10.13039\/501100018623","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2025,3]]},"DOI":"10.1007\/s13042-024-02377-z","type":"journal-article","created":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T10:02:29Z","timestamp":1726221749000},"page":"2057-2071","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Dynamic path planning fusion algorithm with improved A* algorithm and dynamic window approach"],"prefix":"10.1007","volume":"16","author":[{"given":"Jianfeng","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Jielong","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Daxin","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Yufang","family":"Xie","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,13]]},"reference":[{"key":"2377_CR1","doi-asserted-by":"crossref","unstructured":"Karaman S, Walter MR, Perez A, Frazzoli E, Teller S (2011) Anytime motion planning using the rrt. In: 2011 IEEE international conference on robotics and automation. IEEE, pp 1478\u20131483","DOI":"10.1109\/ICRA.2011.5980479"},{"key":"2377_CR2","doi-asserted-by":"crossref","unstructured":"Kuffner JJ, LaValle SM (2000) Rrt-connect: an efficient approach to single-query path planning. In: Proceedings 2000 ICRA. Millennium conference. IEEE international conference on robotics and automation. Symposia proceedings (Cat. No. 00CH37065), vol 2. IEEE, pp 995\u20131001","DOI":"10.1109\/ROBOT.2000.844730"},{"issue":"1","key":"2377_CR3","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1109\/TCYB.2023.3265926","volume":"54","author":"J Fu","year":"2023","unstructured":"Fu J, Sun G, Liu J, Yao W, Wu L (2023) On hierarchical multi-uav dubins traveling salesman problem paths in a complex obstacle environment. IEEE Trans Cybern 54(1):123\u201335","journal-title":"IEEE Trans Cybern"},{"issue":"12","key":"2377_CR4","doi-asserted-by":"publisher","first-page":"24008","DOI":"10.1109\/TITS.2022.3195521","volume":"23","author":"J Fu","year":"2022","unstructured":"Fu J, Sun G, Yao W, Wu L (2022) On trajectory homotopy to explore and penetrate dynamically of multi-uav. IEEE Trans Intell Transport Sys 23(12):24008\u201324019","journal-title":"IEEE Trans Intell Transport Sys"},{"key":"2377_CR5","doi-asserted-by":"crossref","unstructured":"Liu F, He H, Li Z, Guan Z-H, Wang HO (2020) Improved potential field method path planning based on genetic algorithm. In: 2020 39th Chinese control conference (CCC). IEEE, pp 3725\u20133729","DOI":"10.23919\/CCC50068.2020.9189655"},{"key":"2377_CR6","doi-asserted-by":"publisher","first-page":"28322","DOI":"10.1109\/ACCESS.2021.3064831","volume":"10","author":"Q Jin","year":"2021","unstructured":"Jin Q, Tang C, Cai W (2021) Research on dynamic path planning based on the fusion algorithm of improved ant colony optimization and rolling window method. IEEE Access 10:28322\u201328332","journal-title":"IEEE Access"},{"issue":"7","key":"2377_CR7","first-page":"1009","volume":"43","author":"N Yu","year":"2017","unstructured":"Yu N, Wang C, Mo F, Cai J (2017) Dynamic environment path planning based on q-learning algorithm and genetic algorithm. J Beijing Univ Technol 43(7):1009\u20131016","journal-title":"J Beijing Univ Technol"},{"key":"2377_CR8","doi-asserted-by":"publisher","first-page":"21258","DOI":"10.1109\/ACCESS.2021.3056067","volume":"9","author":"M He","year":"2021","unstructured":"He M, Wei Z, Wu X, Peng Y (2021) An adaptive variable neighborhood search ant colony algorithm for vehicle routing problem with soft time windows. IEEE Access 9:21258\u201321266","journal-title":"IEEE Access"},{"key":"2377_CR9","doi-asserted-by":"crossref","unstructured":"Han C, Li B (2023) Mobile robot path planning based on improved a* algorithm. In: 2023 IEEE 11th joint international information technology and artificial intelligence conference (ITAIC), vol 11. IEEE, pp 672\u2013676","DOI":"10.1109\/ITAIC58329.2023.10408799"},{"issue":"1","key":"2377_CR10","doi-asserted-by":"publisher","first-page":"8881684","DOI":"10.1155\/2021\/8881684","volume":"2021","author":"L-S Liu","year":"2021","unstructured":"Liu L-S, Lin J-F, Yao J-X, He D-W, Zheng J-S, Huang J, Shi P (2021) Path planning for smart car based on dijkstra algorithm and dynamic window approach. Wirel Commun Mob Comput 2021(1):8881684","journal-title":"Wirel Commun Mob Comput"},{"key":"2377_CR11","doi-asserted-by":"crossref","unstructured":"Paulino L, Hannum C, Varde AS, Conti CJ (2022) Search methods in motion planning for mobile robots. In: Intelligent systems and applications: proceedings of the 2021 intelligent systems conference (IntelliSys), vol 3. Springer, pp 802\u2013822","DOI":"10.1007\/978-3-030-82199-9_54"},{"issue":"1","key":"2377_CR12","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1109\/100.580977","volume":"4","author":"D Fox","year":"1997","unstructured":"Fox D, Burgard W, Thrun S (1997) The dynamic window approach to collision avoidance. IEEE Robot Autom Mag 4(1):23\u201333","journal-title":"IEEE Robot Autom Mag"},{"issue":"24","key":"2377_CR13","doi-asserted-by":"publisher","first-page":"8312","DOI":"10.3390\/s21248312","volume":"21","author":"J Wu","year":"2021","unstructured":"Wu J, Ma X, Peng T, Wang H (2021) An improved timed elastic band (teb) algorithm of autonomous ground vehicle (agv) in complex environment. Sensors 21(24):8312","journal-title":"Sensors"},{"key":"2377_CR14","doi-asserted-by":"crossref","unstructured":"Mizuno M, Kubota T (2020) A new path planning architecture to consider motion uncertainty in natural environment. In: 2020 IEEE international conference on robotics and automation (ICRA). IEEE, pp 2182\u20132188","DOI":"10.1109\/ICRA40945.2020.9197238"},{"key":"2377_CR15","doi-asserted-by":"crossref","unstructured":"Fnadi M, Du W, Silva RG, Plumet F, Benamar F (2020) Local obstacle-skirting path planning for a fast bi-steerable rover using b\u00e9zier curves. In: 2020 IEEE international conference on robotics and automation (ICRA). IEEE, pp 10242\u201310248","DOI":"10.1109\/ICRA40945.2020.9197563"},{"key":"2377_CR16","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/s10514-020-09947-4","volume":"45","author":"L Chang","year":"2021","unstructured":"Chang L, Shan L, Jiang C, Dai Y (2021) Reinforcement based mobile robot path planning with improved dynamic window approach in unknown environment. Autonom Robots 45:51\u201376","journal-title":"Autonom Robots"},{"key":"2377_CR17","doi-asserted-by":"crossref","unstructured":"Shao L, Li Q, Li C, Sun W (2021) Mobile robot path planning based on improved ant colony fusion dynamic window approach. In: 2021 IEEE international conference on mechatronics and automation (ICMA). IEEE, pp 1100\u20131105","DOI":"10.1109\/ICMA52036.2021.9512795"},{"issue":"1","key":"2377_CR18","doi-asserted-by":"publisher","first-page":"50","DOI":"10.3390\/machines10010050","volume":"10","author":"L Yang","year":"2022","unstructured":"Yang L, Fu L, Li P, Mao J, Guo N (2022) An effective dynamic path planning approach for mobile robots based on ant colony fusion dynamic windows. Machines 10(1):50","journal-title":"Machines"},{"key":"2377_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.oceaneng.2021.108709","volume":"223","author":"H Sang","year":"2021","unstructured":"Sang H, You Y, Sun X, Zhou Y, Liu F (2021) The hybrid path planning algorithm based on improved a* and artificial potential field for unmanned surface vehicle formations. Ocean Eng 223:108709","journal-title":"Ocean Eng"},{"key":"2377_CR20","doi-asserted-by":"publisher","first-page":"19632","DOI":"10.1109\/ACCESS.2021.3052865","volume":"9","author":"L Liu","year":"2021","unstructured":"Liu L, Yao J, He D, Chen J, Huang J, Xu H, Wang B, Guo J (2021) Global dynamic path planning fusion algorithm combining jump-a* algorithm and dynamic window approach. IEEE Access 9:19632\u201319638","journal-title":"IEEE Access"},{"key":"2377_CR21","unstructured":"Yonetani R, Taniai T, Barekatain M, Nishimura M, Kanezaki A (2021) Path planning using neural a* search. In: International conference on machine learning. PMLR, pp 12029\u201312039"},{"issue":"4","key":"2377_CR22","doi-asserted-by":"publisher","first-page":"1748","DOI":"10.1109\/TASE.2020.2976560","volume":"17","author":"J Wang","year":"2020","unstructured":"Wang J, Chi W, Li C, Wang C, Meng MQ-H (2020) Neural rrt*: learning-based optimal path planning. IEEE Trans Autom Sci Eng 17(4):1748\u20131758","journal-title":"IEEE Trans Autom Sci Eng"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-024-02377-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-024-02377-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-024-02377-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T18:28:53Z","timestamp":1739989733000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-024-02377-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,13]]},"references-count":22,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,3]]}},"alternative-id":["2377"],"URL":"https:\/\/doi.org\/10.1007\/s13042-024-02377-z","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,13]]},"assertion":[{"value":"23 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 September 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 September 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}