{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T06:27:32Z","timestamp":1777876052378,"version":"3.51.4"},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Advanced Engineering Informatics"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.aei.2026.104549","type":"journal-article","created":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T09:59:08Z","timestamp":1772704748000},"page":"104549","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Hierarchical area graph for object navigation with adaptive entropy-driven exploration"],"prefix":"10.1016","volume":"73","author":[{"given":"Jing","family":"Xie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dianxi","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fang","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junze","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuetian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Songchang","family":"Jin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.aei.2026.104549_b1","doi-asserted-by":"crossref","unstructured":"Y. Zhu, R. Mottaghi, E. Kolve, J.J. Lim, A. Farhadi, Target-driven visual navigation in indoor scenes using deep reinforcement learning, in: 2017 IEEE International Conference on Robotics and Automation, ICRA, 2017, pp. 3357\u20133364.","DOI":"10.1109\/ICRA.2017.7989381"},{"key":"10.1016\/j.aei.2026.104549_b2","doi-asserted-by":"crossref","first-page":"2608","DOI":"10.1109\/TIP.2023.3263110","article-title":"Multi-object navigation using potential target position policy function","volume":"32","author":"Zeng","year":"2023","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.aei.2026.104549_b3","doi-asserted-by":"crossref","unstructured":"R. Dang, L. Wang, Z. He, S. Su, J. Tang, C. Liu, Q. Chen, Search for or Navigate to? Dual Adaptive Thinking for Object Navigation, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, ICCV, 2023, pp. 8250\u20138259.","DOI":"10.1109\/ICCV51070.2023.00758"},{"key":"10.1016\/j.aei.2026.104549_b4","unstructured":"K. Yadav, R. Ramrakhya, A. Majumdar, V.-P. Berges, S. Kuhar, D. Batra, A. Baevski, O. Maksymets, Offline visual representation learning for embodied navigation, in: Workshop on Reincarnating Reinforcement Learning At ICLR 2023, 2023."},{"key":"10.1016\/j.aei.2026.104549_b5","doi-asserted-by":"crossref","unstructured":"R. Ramrakhya, D. Batra, E. Wijmans, A. Das, PIRLNav: Pretraining with Imitation and RL Finetuning for OBJECTNAV, in: 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, pp. 17896\u201317906.","DOI":"10.1109\/CVPR52729.2023.01716"},{"key":"10.1016\/j.aei.2026.104549_b6","series-title":"Visual semantic navigation using scene priors","author":"Yang","year":"2018"},{"key":"10.1016\/j.aei.2026.104549_b7","series-title":"Computer Vision \u2013 ECCV 2020","first-page":"19","article-title":"Learning object relation graph and tentative policy for visual navigation","author":"Du","year":"2020"},{"key":"10.1016\/j.aei.2026.104549_b8","doi-asserted-by":"crossref","unstructured":"R. Dang, Z. Shi, L. Wang, Z. He, C. Liu, Q. Chen, Unbiased Directed Object Attention Graph for Object Navigation, in: Proceedings of the 30th ACM International Conference on Multimedia, 2022, pp. 3617\u20133627.","DOI":"10.1145\/3503161.3547852"},{"key":"10.1016\/j.aei.2026.104549_b9","doi-asserted-by":"crossref","unstructured":"S. Zhang, X. Song, Y. Bai, W. Li, Y. Chu, S. Jiang, Hierarchical Object-to-Zone Graph for Object Navigation, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, ICCV, 2021, pp. 15130\u201315140.","DOI":"10.1109\/ICCV48922.2021.01485"},{"key":"10.1016\/j.aei.2026.104549_b10","doi-asserted-by":"crossref","unstructured":"R. Fukushima, K. Ota, A. Kanezaki, Y. Sasaki, Y. Yoshiyasu, Object Memory Transformer for Object Goal Navigation, in: 2022 International Conference on Robotics and Automation, ICRA, 2022, pp. 11288\u201311294.","DOI":"10.1109\/ICRA46639.2022.9812027"},{"key":"10.1016\/j.aei.2026.104549_b11","doi-asserted-by":"crossref","unstructured":"H. Du, L. Li, Z. Huang, X. Yu, Object-Goal Visual Navigation via Effective Exploration of Relations Among Historical Navigation States, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2023, pp. 2563\u20132573.","DOI":"10.1109\/CVPR52729.2023.00252"},{"key":"10.1016\/j.aei.2026.104549_b12","doi-asserted-by":"crossref","unstructured":"W. Xie, H. Jiang, S. Gu, J. Xie, Implicit Obstacle Map-driven Indoor Navigation Model for Robust Obstacle Avoidance, in: Proceedings of the 31st ACM International Conference on Multimedia, 2023, pp. 6785\u20136793.","DOI":"10.1145\/3581783.3612100"},{"key":"10.1016\/j.aei.2026.104549_b13","unstructured":"R. Dang, L. Chen, L. Wang, Z. He, C. Liu, Q. Chen, Multiple Thinking Achieving Meta-Ability Decoupling for Object Navigation, in: International Conference on Machine Learning, 2023, pp. 6855\u20136872."},{"issue":"2","key":"10.1016\/j.aei.2026.104549_b14","doi-asserted-by":"crossref","first-page":"2985","DOI":"10.1109\/LRA.2022.3145971","article-title":"Focus on impact: indoor exploration with intrinsic motivation","volume":"7","author":"Bigazzi","year":"2022","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.aei.2026.104549_b15","series-title":"5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2017"},{"key":"10.1016\/j.aei.2026.104549_b16","series-title":"On evaluation of embodied navigation agents","author":"Anderson","year":"2018"},{"key":"10.1016\/j.aei.2026.104549_b17","first-page":"26661","article-title":"No rl, no simulation: Learning to navigate without navigating","volume":"34","author":"Hahn","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.aei.2026.104549_b18","series-title":"Building generalizable agents with a realistic and rich 3d environment","author":"Wu","year":"2018"},{"key":"10.1016\/j.aei.2026.104549_b19","series-title":"Deep learning for embodied vision navigation: A survey","author":"Zhu","year":"2021"},{"key":"10.1016\/j.aei.2026.104549_b20","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1109\/TMM.2021.3070138","article-title":"Deep-irtarget: An automatic target detector in infrared imagery using dual-domain feature extraction and allocation","volume":"24","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Multimed."},{"issue":"8","key":"10.1016\/j.aei.2026.104549_b21","doi-asserted-by":"crossref","first-page":"6735","DOI":"10.1109\/TCSVT.2023.3289142","article-title":"Differential feature awareness network within antagonistic learning for infrared-visible object detection","volume":"34","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.aei.2026.104549_b22","article-title":"Visible-infrared person re-identification with real-world label noise","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.aei.2026.104549_b23","article-title":"A benchmark and frequency compression method for infrared few-shot object detection","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.aei.2026.104549_b24","doi-asserted-by":"crossref","unstructured":"B. Mayo, T. Hazan, A. Tal, Visual Navigation With Spatial Attention, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2021, pp. 16898\u201316907.","DOI":"10.1109\/CVPR46437.2021.01662"},{"key":"10.1016\/j.aei.2026.104549_b25","series-title":"Vtnet: Visual transformer network for object goal navigation","author":"Du","year":"2021"},{"key":"10.1016\/j.aei.2026.104549_b26","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.101889","article-title":"Optimal graph transformer viterbi knowledge inference network for more successful visual navigation","volume":"55","author":"Zhou","year":"2023","journal-title":"Adv. Eng. Informat."},{"key":"10.1016\/j.aei.2026.104549_b27","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102678","article-title":"Learning multimodal adaptive relation graph and action boost memory for visual navigation","volume":"62","author":"Luo","year":"2024","journal-title":"Adv. Eng. Informat."},{"issue":"2","key":"10.1016\/j.aei.2026.104549_b28","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.1109\/TCSVT.2023.3291131","article-title":"Agent-centric relation graph for object visual navigation","volume":"34","author":"Hu","year":"2024","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.aei.2026.104549_b29","article-title":"Temporal scene-object graph learning for object navigation","author":"Chen","year":"2025","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.aei.2026.104549_b30","doi-asserted-by":"crossref","unstructured":"G. Zhou, Y. Hong, Q. Wu, NavGPT: Explicit Reasoning in Vision-and-Language Navigation with Large Language Models, in: AAAI Conference on Artificial Intelligence, 2023.","DOI":"10.1609\/aaai.v38i7.28597"},{"key":"10.1016\/j.aei.2026.104549_b31","series-title":"Gpt-4 technical report","author":"Achiam","year":"2023"},{"key":"10.1016\/j.aei.2026.104549_b32","series-title":"International Conference on Machine Learning","first-page":"42829","article-title":"Esc: Exploration with soft commonsense constraints for zero-shot object navigation","author":"Zhou","year":"2023"},{"key":"10.1016\/j.aei.2026.104549_b33","unstructured":"L.H. Li, P. Zhang, H. Zhang, J. Yang, C. Li, Y. Zhong, L. Wang, L. Yuan, L. Zhang, J.-N. Hwang, K.-W. Chang, J. Gao, Grounded Language-Image Pre-Training, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2022, pp. 10965\u201310975."},{"key":"10.1016\/j.aei.2026.104549_b34","first-page":"32340","article-title":"Zson: Zero-shot object-goal navigation using multimodal goal embeddings","volume":"35","author":"Majumdar","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.aei.2026.104549_b35","series-title":"2024 IEEE International Conference on Robotics and Automation","first-page":"5214","article-title":"Aligning knowledge graph with visual perception for object-goal navigation","author":"Xu","year":"2024"},{"key":"10.1016\/j.aei.2026.104549_b36","doi-asserted-by":"crossref","unstructured":"F. Taioli, F. Cunico, F. Girella, R. Bologna, A. Farinelli, M. Cristani, Language-Enhanced RNR-Map: Querying Renderable Neural Radiance Field Maps with Natural Language, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV) Workshops, 2023, pp. 4669\u20134674.","DOI":"10.1109\/ICCVW60793.2023.00504"},{"key":"10.1016\/j.aei.2026.104549_b37","series-title":"International Conference on Machine Learning","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","author":"Radford","year":"2021"},{"key":"10.1016\/j.aei.2026.104549_b38","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2023.102918","article-title":"Segment anything model for medical image analysis: an experimental study","volume":"89","author":"Mazurowski","year":"2023","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.aei.2026.104549_b39","doi-asserted-by":"crossref","unstructured":"S. Li, L. Ke, M. Danelljan, L. Piccinelli, M. Segu, L.V. Gool, F. Yu, Matching Anything by Segmenting Anything, in: 2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2024, pp. 18963\u201318973.","DOI":"10.1109\/CVPR52733.2024.01794"},{"key":"10.1016\/j.aei.2026.104549_b40","doi-asserted-by":"crossref","unstructured":"A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A.C. Berg, W.-Y. Lo, P. Dollar, R. Girshick, Segment Anything, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, ICCV, 2023, pp. 4015\u20134026.","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"10.1016\/j.aei.2026.104549_b41","doi-asserted-by":"crossref","unstructured":"K. He, X. Zhang, S. Ren, J. Sun, Deep Residual Learning for Image Recognition, in: 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2016, pp. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"10.1016\/j.aei.2026.104549_b42","series-title":"Computer Vision \u2013 ECCV 2020","first-page":"213","article-title":"End-to-end object detection with transformers","author":"Carion","year":"2020"},{"issue":"8","key":"10.1016\/j.aei.2026.104549_b43","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"10.1016\/j.aei.2026.104549_b44","series-title":"Proceedings of the 33rd International Conference on Machine Learning","first-page":"1928","article-title":"Asynchronous methods for deep reinforcement learning","volume":"vol. 48","author":"Mnih","year":"2016"},{"key":"10.1016\/j.aei.2026.104549_b45","series-title":"Ai2-thor: An interactive 3d environment for visual ai","author":"Kolve","year":"2017"},{"key":"10.1016\/j.aei.2026.104549_b46","doi-asserted-by":"crossref","unstructured":"M. Wortsman, K. Ehsani, M. Rastegari, A. Farhadi, R. Mottaghi, Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning, in: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2018, pp. 6743\u20136752.","DOI":"10.1109\/CVPR.2019.00691"},{"key":"10.1016\/j.aei.2026.104549_b47","doi-asserted-by":"crossref","unstructured":"S. Zhang, X. Song, W. Li, Y. Bai, X. Yu, S. Jiang, Layout-Based Causal Inference for Object Navigation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2023, pp. 10792\u201310802.","DOI":"10.1109\/CVPR52729.2023.01039"},{"key":"10.1016\/j.aei.2026.104549_b48","series-title":"Proximal policy optimization algorithms","author":"Schulman","year":"2017"},{"key":"10.1016\/j.aei.2026.104549_b49","series-title":"International Conference on Machine Learning","first-page":"1861","article-title":"Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor","author":"Haarnoja","year":"2018"}],"container-title":["Advanced Engineering Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626002417?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626002417?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T22:13:44Z","timestamp":1777587224000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1474034626002417"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":49,"alternative-id":["S1474034626002417"],"URL":"https:\/\/doi.org\/10.1016\/j.aei.2026.104549","relation":{},"ISSN":["1474-0346"],"issn-type":[{"value":"1474-0346","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Hierarchical area graph for object navigation with adaptive entropy-driven exploration","name":"articletitle","label":"Article Title"},{"value":"Advanced Engineering Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aei.2026.104549","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104549"}}