{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T06:45:00Z","timestamp":1782715500578,"version":"3.54.5"},"reference-count":33,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:00:00Z","timestamp":1782432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100015308","name":"Key Research and Development Program of Xinjiang Uygur Autonomous Region, China","doi-asserted-by":"publisher","award":["2022B01013-2"],"award-info":[{"award-number":["2022B01013-2"]}],"id":[{"id":"10.13039\/501100015308","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Multi-target path planning for Automated Guided Vehicle (AGV) in complex logistics environments requires balancing planning efficiency, obstacle avoidance capability, and trajectory smoothness. To address these challenges, this paper proposes a bi-level collaborative framework integrating Particle Swarm Optimization (PSO) with the Bidirectional Rapidly Exploring Random Tree (Bi-RRT). The framework unifies adaptive sampling, online parameter optimization, and trajectory smoothing within a single planning architecture. Specifically, the framework constructs a five-dimensional particle encoding that includes the expansion step size and multi-level strategy switching thresholds. During the Bi-RRT expansion process, an expansion-failure-driven adaptive sampling mechanism is introduced to enhance search performance in cluttered environments, while local-density-based suppression and directional dispersion are employed to reduce redundant exploration. In addition, a lightweight PSO-based monitoring mechanism enables online adaptive parameter adjustment. For multi-target scheduling, a greedy heuristic based on a hybrid weighted graph determines the visitation sequence. Trajectory smoothness is further improved using cubic B-spline interpolation combined with bounded perturbation optimization. Experimental results demonstrate that the proposed framework improves planning efficiency while maintaining stable performance across environments with different obstacle densities. These results demonstrate the effectiveness of the proposed framework for multi-target AGV path planning in complex warehouse environments.<\/jats:p>","DOI":"10.3390\/s26134062","type":"journal-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T05:49:33Z","timestamp":1782712173000},"page":"4062","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Bi-Level Hybrid Framework for Multi-Target Path Planning of AGV Based on Particle Swarm Optimization and Bidirectional Rapidly Exploring Random Tree"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7064-0316","authenticated-orcid":false,"given":"Tursun","family":"Mamat","sequence":"first","affiliation":[{"name":"Engineering Research Center for Intelligent Transportation, School of Transportation and Logistics Engineering, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China"},{"name":"Key Laboratory of Transportation and Logistics Engineering in Xinjiang, School of Transportation and Logistics Engineering, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8333-949X","authenticated-orcid":false,"given":"Zhaolong","family":"Liu","sequence":"additional","affiliation":[{"name":"Engineering Research Center for Intelligent Transportation, School of Transportation and Logistics Engineering, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China"},{"name":"Key Laboratory of Transportation and Logistics Engineering in Xinjiang, School of Transportation and Logistics Engineering, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiuju","family":"Yang","sequence":"additional","affiliation":[{"name":"Xinjiang Communications Construction Group Co., Ltd., Urumqi 830016, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdukeram","family":"Dolkun","sequence":"additional","affiliation":[{"name":"Engineering Research Center for Intelligent Transportation, School of Transportation and Logistics Engineering, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China"},{"name":"Key Laboratory of Transportation and Logistics Engineering in Xinjiang, School of Transportation and Logistics Engineering, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longfei","family":"Li","sequence":"additional","affiliation":[{"name":"Engineering Research Center for Intelligent Transportation, School of Transportation and Logistics Engineering, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China"},{"name":"Key Laboratory of Transportation and Logistics Engineering in Xinjiang, School of Transportation and Logistics Engineering, Xinjiang Agricultural University, 311 Nongda East Road, Urumqi 830052, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"121510","DOI":"10.1016\/j.eswa.2023.121510","article-title":"An improved fault-tolerant cultural-PSO with probability for multi-AGV path planning","volume":"237","author":"Lin","year":"2024","journal-title":"Expert Syst. 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