{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T07:28:23Z","timestamp":1772782103192,"version":"3.50.1"},"reference-count":22,"publisher":"Cambridge University Press (CUP)","issue":"6","license":[{"start":{"date-parts":[[2021,10,4]],"date-time":"2021-10-04T00:00:00Z","timestamp":1633305600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotica"],"published-print":{"date-parts":[[2022,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In order to improve the speed of motion planning, this paper proposes an improved RRTConnect algorithm (SDPS-RRTConnect) based on sparse dead point saved strategy. Combining sparse expansion strategy and dead point saved strategy, the algorithm can reduce the number of collision detection, fast convergence, avoid falling into local minimum, and ensure the completeness of search space. The algorithm is simulated in different environments. The results show that in complex environments, the sparse dead point saved strategy plays a good effect. In simple environments, the greedy connection strategy works well. Compared with the standard RRT algorithm, the standard RRTConnect algorithm, and the SDPS-RRT algorithm, the SDPS-RRTConnect algorithm has the shortest planning time, and it is suitable for both simple and complex environments. The 500 experiments show that the algorithm has strong robustness. The actual robot experiments show that the path planned by SDPS-RRTConnect algorithm is effective.<\/jats:p>","DOI":"10.1017\/s0263574721001417","type":"journal-article","created":{"date-parts":[[2021,10,4]],"date-time":"2021-10-04T18:14:34Z","timestamp":1633371274000},"page":"1855-1867","source":"Crossref","is-referenced-by-count":7,"title":["Effective motion planning of manipulator based on SDPS-RRTConnect"],"prefix":"10.1017","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5377-2683","authenticated-orcid":false,"given":"Junxiang","family":"Xu","sequence":"first","affiliation":[]},{"given":"Jiwu","family":"Wang","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2021,10,4]]},"reference":[{"key":"S0263574721001417_ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s11370-019-00281-y"},{"key":"S0263574721001417_ref15","doi-asserted-by":"publisher","DOI":"10.1177\/02783640122067453"},{"key":"S0263574721001417_ref18","doi-asserted-by":"publisher","DOI":"10.3390\/s18020571"},{"key":"S0263574721001417_ref11","first-page":"20","article-title":"A Comparison of RRT, RRT* and RRT*-Smart Path Planning Algorithms","volume":"16","author":"Iram","year":"2016","journal-title":"Int. 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Soft Comput."},{"key":"S0263574721001417_ref14","unstructured":"14. Kuffner, J. J. and Lavalle, S. M. , \u201cRRT-connect: An efficient approach to single-query path planning,\u201d In Proceedingsof the IEEE International Conference on Robotics and Automation, San Francisco, CA, USA, 24\u201328 April, 995\u20131001 (2020)."},{"key":"S0263574721001417_ref2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2965418"},{"key":"S0263574721001417_ref17","doi-asserted-by":"publisher","DOI":"10.3390\/app10041381"},{"key":"S0263574721001417_ref9","doi-asserted-by":"publisher","DOI":"10.1177\/0278364911406761"},{"key":"S0263574721001417_ref10","doi-asserted-by":"publisher","DOI":"10.5772\/56718"},{"key":"S0263574721001417_ref12","doi-asserted-by":"crossref","unstructured":"12. Weghe, M. V. , Ferguson, D. and Srinivasa, S. 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Soft Comput."},{"key":"S0263574721001417_ref1","unstructured":"1. Kim, M. , Kim, J. , Shin, D. and Jin, M. , \u201cRobot-based Shoe Manufacturing System,\u201d In Proceedings of the 18th International Conference on Control, Automation and Systems (ICCAS), Daegwallyeong, Korea, 1491\u20131494 (2018)."},{"key":"S0263574721001417_ref22","doi-asserted-by":"publisher","DOI":"10.1177\/1729881419865427"}],"container-title":["Robotica"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0263574721001417","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T08:29:14Z","timestamp":1725870554000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0263574721001417\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,4]]},"references-count":22,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["S0263574721001417"],"URL":"https:\/\/doi.org\/10.1017\/s0263574721001417","relation":{},"ISSN":["0263-5747","1469-8668"],"issn-type":[{"value":"0263-5747","type":"print"},{"value":"1469-8668","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,4]]}}}