{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T16:47:25Z","timestamp":1777394845185,"version":"3.51.4"},"reference-count":27,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T00:00:00Z","timestamp":1777248000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Path planning for inspection and maintenance robots in nuclear power plants often suffers from limited adaptability, high computational cost, and unstable convergence in obstacle-dense confined environments. To address these issues, this paper proposes an improved Bi-RRT\u2013APF path optimization framework for complex industrial scenarios. The method integrates (1) a hybrid sampling strategy combining random, goal-biased, and potential-field-guided sampling to enhance global exploration and convergence efficiency; (2) a potential-field-guided perturbation and stagnation detection mechanism to improve escape capability from local minima; and (3) a dynamic target switching and constrained segmented connection strategy to improve path feasibility and safety. A digital twin-based simulation platform is further developed to validate the engineering applicability of the proposed approach. Simulation results demonstrate significant quantitative improvements over baseline methods. Compared with conventional RRT and Bi-RRT, the proposed method reduces iteration count by 65.3% and 43.8%, respectively, and decreases computation time by 76.1% and 48.4%, respectively, while increasing the success rate to 95% (from 82% and 93%) and improving path smoothness (reduced from 5.3 and 3.3 to 2.9). Compared with advanced variants (Quad-RRT and KB-RRT*), the method further reduces computation time by 25.2% and 10.3% and iteration count by 29.3% and 8.4%, respectively. These results indicate that the proposed method achieves a balanced improvement in efficiency, robustness, and path quality. This work provides an efficient and reliable solution for autonomous path planning of robots in complex nuclear power plant environments.<\/jats:p>","DOI":"10.3390\/a19050337","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T09:55:39Z","timestamp":1777370139000},"page":"337","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Path Optimization Simulation Method for Nuclear Power Plant Inspection and Maintenance Robots Based on the Integration of Bi-RRT and APF"],"prefix":"10.3390","volume":"19","author":[{"given":"Tong","family":"Wu","sequence":"first","affiliation":[{"name":"CNNC Hexin Information Technology (Beijing) Co., Ltd., Beijing 100091, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meihao","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China"},{"name":"Nuclear Industry X Intelligence Laboratory, Beijing University of Technology, Beijing 100124, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4559-1002","authenticated-orcid":false,"given":"Zhansheng","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China"},{"name":"Nuclear Industry X Intelligence Laboratory, Beijing University of Technology, Beijing 100124, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China"},{"name":"Nuclear Industry X Intelligence Laboratory, Beijing University of Technology, Beijing 100124, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fengjuan","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China"},{"name":"Nuclear Industry X Intelligence Laboratory, Beijing University of Technology, Beijing 100124, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3226-0099","authenticated-orcid":false,"given":"Xiaoqing","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China"},{"name":"Nuclear Industry X Intelligence Laboratory, Beijing University of Technology, Beijing 100124, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haowen","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China"},{"name":"Nuclear Industry X Intelligence Laboratory, Beijing University of Technology, Beijing 100124, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"CNNC Hexin Information Technology (Beijing) Co., Ltd., Beijing 100091, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahao","family":"Wu","sequence":"additional","affiliation":[{"name":"CNNC Hexin Information Technology (Beijing) Co., Ltd., Beijing 100091, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"101750","DOI":"10.1016\/j.softx.2024.101750","article-title":"End to end navigation stack for nuclear power plant inspection with mobile robot","volume":"26","year":"2024","journal-title":"SoftwareX"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.net.2023.09.007","article-title":"The planning strategy of robotics technology for nuclear decommissioning in Taiwan","volume":"56","author":"Tu","year":"2024","journal-title":"Nucl. 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