{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T09:52:02Z","timestamp":1777024322571,"version":"3.51.4"},"reference-count":18,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:00:00Z","timestamp":1767830400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:00:00Z","timestamp":1767830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62273124"],"award-info":[{"award-number":["62273124"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017599","name":"Science and Technology Program of Zhejiang Province","doi-asserted-by":"publisher","award":["2025C01183"],"award-info":[{"award-number":["2025C01183"]}],"id":[{"id":"10.13039\/501100017599","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Engineering with Computers"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1007\/s00366-025-02239-4","type":"journal-article","created":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T12:11:51Z","timestamp":1767874311000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A novel low risk trajectory planning method via pool of radom optimal routes"],"prefix":"10.1007","volume":"42","author":[{"given":"Yumeng","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangyu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wujia","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,8]]},"reference":[{"key":"2239_CR1","first-page":"6695","volume":"ICRA","author":"Y Chen","year":"2024","unstructured":"Chen Y, Arkin J, Dawson C, Zhang Y, Roy N, Fan C (2024) AutoTAMP: Autoregressive task and motion planning with LLMs as translators and checkers. Proc IEEE Int Conf Robot Autom ICRA:6695\u20136702","journal-title":"Proc IEEE Int Conf Robot Autom"},{"key":"2239_CR2","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1016\/j.jmsy.2021.10.008","volume":"61","author":"M Ronzoni","year":"2021","unstructured":"Ronzoni M, Accorsi R, Botti L, Manzini R (2021) A support-design framework for cooperative robots systems in labor-intensive manufacturing processes. J Manuf Syst 61:646\u2013657","journal-title":"J Manuf Syst"},{"issue":"1","key":"2239_CR3","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1049\/iet-csr.2018.0003","volume":"1","author":"Y Yang","year":"2019","unstructured":"Yang Y, Pan J, Wan W (2019) Survey of optimal motion planning. IET Cyber-Syst Robot 1(1):13\u201319","journal-title":"IET Cyber-Syst Robot"},{"key":"2239_CR4","first-page":"9247","volume":"IROS","author":"S Guo","year":"2021","unstructured":"Guo S, Liu B, Zhang S, Guo J, Wang C (2021) Continuous-time Gaussian Process Trajectory Generation for Multi-robot Formation via Probabilistic Inference. Proc IEEE\/RSJ Int Conf Intell Robots Syst IROS:9247\u20139253","journal-title":"Proc IEEE\/RSJ Int Conf Intell Robots Syst"},{"issue":"9\u201310","key":"2239_CR5","doi-asserted-by":"publisher","first-page":"1164","DOI":"10.1177\/0278364913488805","volume":"32","author":"M Zucker","year":"2013","unstructured":"Zucker M, Ratliff N, Dragan AD, Pivtoraiko M, Klingensmith M, Dellin CM, Bagnell JA, Srinivasa SS (2013) CHOMP: Covariant Hamiltonian optimization for motion planning. Int J Robot Res 32(9\u201310):1164\u20131193","journal-title":"Int J Robot Res"},{"issue":"9","key":"2239_CR6","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.1177\/0278364914528132","volume":"33","author":"J Schulman","year":"2014","unstructured":"Schulman J, Duan Y, Ho J, Lee A, Awwal I, Bradlow H, Pan J, Patil S, Goldberg K, Abbeel P (2014) Motion planning with sequential convex optimization and convex collision checking. Int J Robot Res 33(9):1251\u20131270","journal-title":"Int J Robot Res"},{"key":"2239_CR7","unstructured":"Toussaint M (2014) \u201cNewton methods for k-order markov constrained motion problems,\u201d arXiv preprint arXiv:1407.0414"},{"issue":"11","key":"2239_CR8","doi-asserted-by":"publisher","first-page":"1319","DOI":"10.1177\/0278364918790369","volume":"37","author":"M Mukadam","year":"2018","unstructured":"Mukadam M, Dong J, Yan X, Dellaert F, Boots B (2018) Continuous-time Gaussian process motion planning via probabilistic inference. Int J Robot Res 37(11):1319\u20131340","journal-title":"Int J Robot Res"},{"issue":"8","key":"2239_CR9","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1177\/0278364920918296","volume":"39","author":"T Osa","year":"2020","unstructured":"Osa T (2020) Multimodal trajectory optimization for motion planning. Int J Robot Res 39(8):983\u20131001","journal-title":"Int J Robot Res"},{"key":"2239_CR10","first-page":"4294","volume":"IROS","author":"M Ewerton","year":"2019","unstructured":"Ewerton M, Maeda G, Koert D, Kolev Z, Takahashi M, Peters J (2019) Reinforcement Learning of Trajectory Distributions: Applications in Assisted Teleoperation and Motion Planning. Proc IEEE\/RSJ Int Conf Intell Robots Syst IROS:4294\u20134300","journal-title":"Proc IEEE\/RSJ Int Conf Intell Robots Syst"},{"key":"2239_CR11","unstructured":"Ren T, Xiao C, Zhang T, Li N, Wang Z, Sanghavi S, Schuurmans D, Dai B (2022) \u201cLatent Variable Representation for Reinforcement Learning,\u201d arXiv preprint arXiv:2212.08765"},{"key":"2239_CR12","doi-asserted-by":"publisher","first-page":"4569","DOI":"10.1109\/ICRA.2011.5980280","volume":"ICRA","author":"M Kalakrishnan","year":"2011","unstructured":"Kalakrishnan M, Chitta S, Theodorou E, Pastor P, Schaal S (2011) STOMP: Stochastic trajectory optimization for motion planning. Proc IEEE Int Conf Robot Autom ICRA:4569\u20134574","journal-title":"Proc IEEE Int Conf Robot Autom"},{"issue":"1","key":"2239_CR13","first-page":"1","volume":"12","author":"A Doucet","year":"2001","unstructured":"Doucet A, De Freitas N, Gordon N (2001) An introduction to Monte Carlo methods for Bayesian filtering. Signal Process 12(1):1\u20133","journal-title":"Signal Process"},{"key":"2239_CR14","unstructured":"Kober J, Peters J (2008) Policy search for motor primitives in robotics. Advances in neural information processing systems 21"},{"key":"2239_CR15","unstructured":"Beal MJ (2003) Variational algorithms for approximate Bayesian inference, Univ. London, Queen Mary"},{"key":"2239_CR16","first-page":"727","volume":"RO-MAN","author":"L Koutras","year":"2020","unstructured":"Koutras L, Doulgeri Z (2020) A novel DMP formulation for global and frame independent spatial scaling in the task space. Proc IEEE Int Conf Robot Hum Interact Commun RO-MAN:727\u2013732","journal-title":"Proc IEEE Int Conf Robot Hum Interact Commun"},{"key":"2239_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2021.103844","volume":"144","author":"M Ginesi","year":"2021","unstructured":"Ginesi M, Sansonetto N, Fiorini P (2021) Overcoming some drawbacks of dynamic movement primitives. Robot Auton Syst 144:103844","journal-title":"Robot Auton Syst"},{"key":"2239_CR18","doi-asserted-by":"crossref","unstructured":"Kalakrishnan M, Chitta S, Theodorou E, Pastor p, Schaal S (2011) STOMP: STOMP: Stochastic trajectory optimization for motion planning, Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pp. 4569\u20134574","DOI":"10.1109\/ICRA.2011.5980280"}],"container-title":["Engineering with Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00366-025-02239-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00366-025-02239-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00366-025-02239-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T09:00:22Z","timestamp":1777021222000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00366-025-02239-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,8]]},"references-count":18,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["2239"],"URL":"https:\/\/doi.org\/10.1007\/s00366-025-02239-4","relation":{},"ISSN":["0177-0667","1435-5663"],"issn-type":[{"value":"0177-0667","type":"print"},{"value":"1435-5663","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,8]]},"assertion":[{"value":"27 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declared that they have no Conflict of interest to this work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"6"}}