| dc.contributor | 資訊系 | |
| dc.creator (作者) | 劉吉軒 | |
| dc.creator (作者) | Liu, Jyi-Shane;Ma, Chi-Wei;Lee, Gong-Yi | |
| dc.date (日期) | 2023-08 | |
| dc.date.accessioned | 7-一月-2025 09:36:44 (UTC+8) | - |
| dc.date.available | 7-一月-2025 09:36:44 (UTC+8) | - |
| dc.date.issued (上傳時間) | 7-一月-2025 09:36:44 (UTC+8) | - |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/155079 | - |
| dc.description.abstract (摘要) | This research aims to design a spatial model that describes the task space and records object location information required by UAVs for autonomous navigation in task execution. This model enables UAVs to integrate pre-defined layout information of a given task space with the on-site observed object location information during task execution. Autonomous navigation is then realized by visual sensing and dynamic path planning based on task requirement. To this extent, UAVs can produce and maintain more effective navigation path, reduce unnecessary flight time, and thereby increase task efficiency. | |
| dc.format.extent | 111 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Proceedings of The 11th International Conference on Advanced Robotics and Intelligent Systems (ARIS 2023), National Taiwan University of Science and Technology | |
| dc.subject (關鍵詞) | Visualization; Navigation; Layout; Robot sensing systems; Path planning; Sensors; Task analysis | |
| dc.title (題名) | Intelligent Spatial Modeling for Autonomous Drone Navigation Enhancement | |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.1109/ARIS59192.2023.10268570 | |
| dc.doi.uri (DOI) | https://doi.org/10.1109/ARIS59192.2023.10268570 | |
