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Nonetheless, the prevalent reliance of vSLAM technology on the assumption of static environments has led to suboptimal performance in practical implementations, particularly in unstructured and dynamically noisy environments such as substations. Despite advancements in mitigating the influence of dynamic objects through the integration of geometric and semantic information, existing approaches have struggled to strike an equilibrium between performance and real-time responsiveness. This study introduces a lightweight, multi-modal semantic framework predicated on vSLAM, designed to enable intelligent robots to adeptly navigate the dynamic environments characteristic of substations. The framework notably enhances vSLAM performance by mitigating the impact of dynamic objects through a synergistic combination of object detection and instance segmentation techniques. Initially, an enhanced lightweight instance segmentation network is deployed to ensure both the real-time responsiveness and accuracy of the algorithm. Subsequently, the algorithm\u2019s performance is further refined by amalgamating the outcomes of detection and segmentation processes. With a commitment to maximising performance, the framework also ensures the algorithm\u2019s real-time capability. Assessments conducted on public datasets and through empirical experiments have demonstrated that the proposed method markedly improves both the accuracy and real-time performance of vSLAM in dynamic environments.<\/jats:p>","DOI":"10.1017\/s0263574724000511","type":"journal-article","created":{"date-parts":[[2024,4,19]],"date-time":"2024-04-19T07:50:52Z","timestamp":1713513052000},"page":"2169-2183","source":"Crossref","is-referenced-by-count":10,"title":["A visual SLAM-based lightweight multi-modal semantic framework for an intelligent substation robot"],"prefix":"10.1017","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-8495-9468","authenticated-orcid":false,"given":"Shaohu","family":"Li","sequence":"first","affiliation":[]},{"given":"Jason","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Zhijun","family":"Li","sequence":"additional","affiliation":[]},{"given":"Shaofeng","family":"Li","sequence":"additional","affiliation":[]},{"given":"Bixiang","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Shangbing","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Feng","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Yuwei","family":"Yang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8384-0002","authenticated-orcid":false,"given":"Guoxin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Lanfang","family":"Dong","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2024,4,19]]},"reference":[{"key":"S0263574724000511_ref13","doi-asserted-by":"crossref","unstructured":"[13] Liu, Y. and Miura, J. , \u201cKMOP-vSLAM: Dynamic Visual SLAM for RGB-D Cameras using K-means and OpenPose,\u201d In:\u00a0Proceedings of the IEEE\/SICE International Symposium on System Integration (SII), (2021) pp. 415\u2013420.","DOI":"10.1109\/IEEECONF49454.2021.9382724"},{"key":"S0263574724000511_ref20","doi-asserted-by":"publisher","DOI":"10.1108\/RIA-09-2022-0226"},{"key":"S0263574724000511_ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3010942"},{"key":"S0263574724000511_ref30","unstructured":"[30] Li, H. , Li, J. , Wei, H. , Liu, Z. , Zhan, Z. and Ren, Q. , \u201cSlim-neck by GSConv: A better design paradigm of detector architectures for autonomous vehicles,\u201d (2022). arXiv preprint, 2022 arXiv:\u00a02206.02424."},{"key":"S0263574724000511_ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2017.7510364"},{"key":"S0263574724000511_ref7","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574720001046"},{"key":"S0263574724000511_ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"S0263574724000511_ref29","doi-asserted-by":"crossref","unstructured":"[29] Dumitriu, A. , Tatui, F. , Miron, F. , Ionescu, R. 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