Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments
Autonomous navigation plays a crucial role in cutting-edge scientific and technological domains, such as autonomous driving and space exploration. Current models often rely on knowledge of the discharge patterns of navigation cells in living organisms (e.g. place/grid cells) to encode spatial inform...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-08-01
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| Series: | Geo-spatial Information Science |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2025.2541878 |
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| author | Donghui Han Tong Qin Tianyu Yang Hua Liao Qiaosong Hei Fangwen Yu Bailu Si Weihua Dong |
| author_facet | Donghui Han Tong Qin Tianyu Yang Hua Liao Qiaosong Hei Fangwen Yu Bailu Si Weihua Dong |
| author_sort | Donghui Han |
| collection | DOAJ |
| description | Autonomous navigation plays a crucial role in cutting-edge scientific and technological domains, such as autonomous driving and space exploration. Current models often rely on knowledge of the discharge patterns of navigation cells in living organisms (e.g. place/grid cells) to encode spatial information, which works well in ideal environments. However, real-world autonomous navigation presents greater challenges due to complex and dynamic geospatial information, leading to issues such as low robustness, poor interpretability, and high energy consumption for existing models. To address these challenges, it is essential to explore the roles and functional connectivity of distinct brain regions involved in processing real-world geospatial information and integrate these insights into autonomous navigation algorithms. This paper reviews empirical studies using neuroscientific techniques to investigate how the human brain processes geographical information during navigation. In particular, we discuss opportunities and challenges associated with three critical aspects: (1) expanding the understanding of cognitive mechanisms from isolated regional functions to integrated functional connectivity and large-scale brain networks, (2) refining neurocognitive experiments to provide ecologically valid evidence in complex and dynamic contexts and (3) developing efficient approaches to computationally mimic and implement spatial cognition mechanisms of human brain in navigation algorithms. Addressing these difficulties would not only enable machines to navigate autonomously and effectively in complex real-world and extreme environments (e.g. space and the deep sea) but also pave the way for the development of future intelligent systems (e.g. GeoAI) with human-like cognitive capabilities. |
| format | Article |
| id | doaj-art-6c6af4dd7f1d4d2e91e4c6628b1beeab |
| institution | Kabale University |
| issn | 1009-5020 1993-5153 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj-art-6c6af4dd7f1d4d2e91e4c6628b1beeab2025-08-20T03:59:36ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532025-08-0111610.1080/10095020.2025.2541878Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environmentsDonghui Han0Tong Qin1Tianyu Yang2Hua Liao3Qiaosong Hei4Fangwen Yu5Bailu Si6Weihua Dong7Faculty of Geographical Science, Beijing Normal University, Beijing, ChinaResearch Group CartoGIS, Department of Geography, Ghent University, Ghent, BelgiumFaculty of Geographical Science, Beijing Normal University, Beijing, ChinaSchool of Geographic Sciences, Hunan Normal University, Changsha, ChinaFaculty of Geographical Science, Beijing Normal University, Beijing, ChinaCenter for Brain-Inspired Computing Research (CBICR), Tsinghua University, Beijing, ChinaSchool of Systems Science, Beijing Normal University, Beijing, ChinaFaculty of Geographical Science, Beijing Normal University, Beijing, ChinaAutonomous navigation plays a crucial role in cutting-edge scientific and technological domains, such as autonomous driving and space exploration. Current models often rely on knowledge of the discharge patterns of navigation cells in living organisms (e.g. place/grid cells) to encode spatial information, which works well in ideal environments. However, real-world autonomous navigation presents greater challenges due to complex and dynamic geospatial information, leading to issues such as low robustness, poor interpretability, and high energy consumption for existing models. To address these challenges, it is essential to explore the roles and functional connectivity of distinct brain regions involved in processing real-world geospatial information and integrate these insights into autonomous navigation algorithms. This paper reviews empirical studies using neuroscientific techniques to investigate how the human brain processes geographical information during navigation. In particular, we discuss opportunities and challenges associated with three critical aspects: (1) expanding the understanding of cognitive mechanisms from isolated regional functions to integrated functional connectivity and large-scale brain networks, (2) refining neurocognitive experiments to provide ecologically valid evidence in complex and dynamic contexts and (3) developing efficient approaches to computationally mimic and implement spatial cognition mechanisms of human brain in navigation algorithms. Addressing these difficulties would not only enable machines to navigate autonomously and effectively in complex real-world and extreme environments (e.g. space and the deep sea) but also pave the way for the development of future intelligent systems (e.g. GeoAI) with human-like cognitive capabilities.https://www.tandfonline.com/doi/10.1080/10095020.2025.2541878Brain-inspired navigationgeospatial cognitionmechanismscognitive experimentcomputational model |
| spellingShingle | Donghui Han Tong Qin Tianyu Yang Hua Liao Qiaosong Hei Fangwen Yu Bailu Si Weihua Dong Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments Geo-spatial Information Science Brain-inspired navigation geospatial cognition mechanisms cognitive experiment computational model |
| title | Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments |
| title_full | Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments |
| title_fullStr | Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments |
| title_full_unstemmed | Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments |
| title_short | Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments |
| title_sort | geospatial brain inspired navigation a neurocognitive approach for autonomous systems in complex environments |
| topic | Brain-inspired navigation geospatial cognition mechanisms cognitive experiment computational model |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2025.2541878 |
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