{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T03:47:39Z","timestamp":1785901659901,"version":"3.56.0"},"reference-count":51,"publisher":"Wiley","issue":"14","license":[{"start":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T00:00:00Z","timestamp":1783814400000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Concurrency and Computation"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Aiming at the problems of slow convergence speed and low computational efficiency in robot path planning in dynamic environments, a combination of swarm intelligence optimization algorithm is proposed to solve the above problems. Swarm intelligence optimization algorithms have garnered significant attention for addressing complex engineering challenges, owing to their inherent robustness and flexibility. Among these, the Painted Kingfisher Optimization (PKO) is a recently developed metaheuristic recognized for its structural simplicity and rapid convergence. However, when tackling high\u2010dimensional or non\u2010linear tasks, the original PKO often suffers from stagnation in population diversity and a tendency to become trapped in local optima, which limits its optimization precision in complex landscapes. To surmount these deficiencies, this paper proposes a multi\u2010strategy Improved Painted Kingfisher Optimization (IPKO) algorithm. The proposed framework incorporates a multi\u2010dimensional initialization strategy based on quantum computing to enhance population diversity and utilizes a dynamic mutation mechanism of quantum gates to refine population quality. Furthermore, an attenuation factor E and a joiner strategy derived from the Sparrow Search Algorithm (SSA) are integrated into the symbiotic phase to accelerate convergence toward optimal regions. The performance of IPKO was rigorously evaluated against multiple state\u2010of\u2010the\u2010art algorithms using the CEC2021 (10 functions) and CEC2022 (12 functions) test suites. Experimental results demonstrate that IPKO significantly outperforms its competitors across the majority of benchmark cases. Finally, the practical utility of IPKO is validated through its application to autonomous robot navigation and multi\u2010robot dynamic path planning. Compared to the original PKO, IPKO consistently yields superior optimal and average path lengths in both simple and complex scenarios. Notably, in multi\u2010robot dynamic tasks, the maximum single\u2010step time of IPKO decreased by approximately 15% and 20% in Scenarios 1 and 3, respectively. In Scenario 2, the average decision time was reduced from 0.1269\u2009s\/step (PKO) to 0.0891\u2009s\/step (IPKO), representing a significant enhancement of 29.8%.<\/jats:p>","DOI":"10.1002\/cpe.70740","type":"journal-article","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T03:08:15Z","timestamp":1783912095000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Application of an Improved Swarm Optimization in Robot Autonomous Navigation System"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-8526-0263","authenticated-orcid":false,"given":"Yi","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Electrical and Computer Science Jilin Jianzhu University  Changchun China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoran","family":"Li","sequence":"additional","affiliation":[{"name":"College of Electrical and Computer Science Jilin Jianzhu University  Changchun China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifei","family":"Cai","sequence":"additional","affiliation":[{"name":"College of International Energy Jinan University  Zhuhai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Electrical and Computer Science Jilin Jianzhu University  Changchun China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianshu","family":"You","sequence":"additional","affiliation":[{"name":"College of Electrical and Computer Science Jilin Jianzhu University  Changchun China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7260-1743","authenticated-orcid":false,"given":"Yong","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Electrical and Computer Science Jilin Jianzhu University  Changchun 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