請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/51808
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳世銘(Suming Chen) | |
dc.contributor.author | Te-Hung Lu | en |
dc.contributor.author | 盧德鴻 | zh_TW |
dc.date.accessioned | 2021-06-15T13:50:54Z | - |
dc.date.available | 2020-10-12 | |
dc.date.copyright | 2015-10-12 | |
dc.date.issued | 2015 | |
dc.date.submitted | 2015-10-07 | |
dc.identifier.citation | 林慧美、陳世銘、楊宜璋、杜威霆、李柔靜、陳毓良、陳俊吉、蔡錦銘。2007。導入無線射頻技術於溫室種苗精準栽培與生產履歷之研究。出自“2007農機與生機論文發表會論文摘要集 ”,41-42。臺北:中華農業機械學會。
岳基隆、張慶杰、朱華勇。2010。微小型四旋翼無人機研究進展及關鍵技術淺析。 電光與控制 17(10):46-52。 徐上為、廖國基、陳世銘、鄭宇帆、陳毓良。2010。應用太陽能輔助熱泵系統於植物工廠之整合控制與效能分析。出自“2010年農機與生機科技論文發表會論文集”,788-792。屏東:中華農業機械學會。 陳世銘、吳德輝、楊智凱、蔡養正、黃政偉、繆八龍。2002。稻株含氮量遙測系統之開發。出自“應用於水稻精準農業體系之知識與技術”,113-128。臺北:行政院農業委員會農業試驗所。 陳世銘、謝廣文、黃裕益、楊宜璋、陳加增、呂宏志、張晉倫、林慧美、陳毓良、陳俊吉。2007。溫室遠端監控及精準栽培自動化之研究。出自”2007 農業資訊科技應用研討會論文集”,64-75。臺北:財團法人臺灣農業資訊科技發展協會。 陳世銘。2010。植物工廠國內外現況及技術檢討。出自“臺灣推動植物工廠之展望研討會論文集”。 臺北:國立臺灣大學生物能源研究中心。 陳世銘、方煒、羅筱鳳、曹幸之、張耀乾、廖國基、顏炳郎、蔡兆胤。2011。臺灣植物工廠現況與發展策略之分析。農業機械學刊 20(4):95-106。 陳育菘、陳世銘、楊宜璋、鄭宇帆、林佳吟、葉德銘、謝瑞旻。2007。以LED可調系統於龍膽組培苗最適光環境之分析。出自“2007 農機與生機論文發表會論文摘要集”,43-44。臺北:中華農業機械學會。 陳金男、陳世銘、楊宜璋、李進發。2003。以發光二極體作為組織培養光源之光環境模擬。出自“九十二年農機與生機論文發表會論文摘要集”,125-126。臺北:中華農業機械學會。 陳健智。2013。建立以日累積光合作用量為基準之補光系統應用於太陽光與人工光源併用型植物工廠。 碩士論文。臺北:國立臺灣大學生物產業機電工程學研究所。 謝幸宜、邱式鴻。2013。以自率光束法提升四旋翼 UAV 航拍影像之空三平差精度。航測及遙測學刊 16(4):245-260。 劉乾、孫志鋒。2011。基于ARM的四旋翼無人飛行器控制系统。機電工程 10:1237-1240。 Anderson, S. B., and V. Lebacqz. 1997. Historical overview of V/STOL aircraft technology. Argentim, L. M., W. C. Rezende, P. E. Santos, and R. A. Aguiar. 2013. PID, LQR and LQR-PID on a quadcopter platform. In Informatics, Electronics Vision (ICIEV), 2013 International Conference on. IEEE. Auernhammer, H. 2001. Precision farming—the environmental challenge. Computers and electronics in agriculture 30(1):31-43. Baggio, A. 2005. Wireless sensor networks in precision agriculture. In ACM Workshop on Real-World Wireless Sensor Networks (REALWSN 2005), Stockholm, Sweden. Barnes, C., T. Tibbitts, J. Sager, G. Deitzer, D. Bubenheim, G. Koerner, and B. Bugbee. 1993. Accuracy of quantum sensors measuring yield photon flux and photosynthetic photon flux. HortScience 28(12):1197-1200. Bouabdallah, S., M. Becker, and R. Siegwart. 2007. Autonomous miniature flying robots: coming soon!-research, development, and results. Robotics Automation Magazine, IEEE 14(3):88-98. Bouabdallah, S., P. Murrieri, and R. Siegwart. 2004a. Design and control of an indoor micro quadrotor. In Robotics and Automation, 2004. Proceedings. ICRA'04. 2004 IEEE International Conference on. IEEE. Bouabdallah, S., A. Noth, and R. Siegwart. 2004b. PID vs LQ control techniques applied to an indoor micro quadrotor. In Intelligent Robots and Systems, 2004.(IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on. IEEE. Chen, S. 2010. Current status of plant factories in Taiwan and future development. In “Proceedings of 2010 Annual Meeting of Japanese Society of Agricultural, Biological and Environmental Engineers and Scientists (JSABEES)”, Invited Speech, P. 302-308. Kyoto, Japan: Kyoto University. Chen S., I. C. Yang, K. W. Hsieh, Y. I. Huang, C. Y. Tsai, and Y. L. Chen. 2011.RFID-integrated remote sensing system for greenhouse production. In “Proceedings CD of CIGR International Symposium on ‘Sustainable Bioproduction - Water, Energy, and Food’ (CIGR 2011)”, Invited Speech, Paper No. 22DG06. Tokyo, Japan: Tower Hall Funabori. de Marina, H. G., F. J. Pereda, J. M. Giron-Sierra, and F. Espinosa. 2012. UAV attitude estimation using unscented kalman filter and TRIAD. Industrial Electronics, IEEE Transactions on 59(11):4465-4474. Fielder, P., and P. Comeau. 2000. Construction and testing of an inexpensive PAR Sensor. Res. Br., Min. For., Victoria, BC. Work.–Pap 53. Hanafi, D., M. Qetkeaw, R. Ghazali, M. N. M. Than, W. M. Utomo, and R. Omar. 2013. Simple GUI Wireless Controller of Quadcopter. Int'l J. of Communications, Network and System Sciences 6:52. Hamamatsu Photodiode Technical Information, Hamamatsu Photonics K. K., Hamamatsu City, Japan Jeremia, S., E. Kuantama, and J. Pangaribuan. 2012. Design and construction of remote-controlled quad-copter based on STC12C5624AD. In System Engineering and Technology (ICSET), 2012 International Conference on. IEEE. Kushleyev, A., D. Mellinger, C. Powers, and V. Kumar. 2013. Towards a swarm of agile micro quadrotors. Autonomous Robots 35(4):287-300. Leong, B. T. M., S. M. Low, and M. P.-L. Ooi. 2012. Low-Cost Microcontroller-based Hover Control Design of a Quadcopter. Procedia Engineering 41:458-464. Mahony, R., T. Hamel, and J.-M. Pflimlin. 2005. Complementary filter design on the special orthogonal group SO (3). In Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC'05. 44th IEEE Conference on. IEEE. MESA. 2009. PAR Sensor Operating Instructions. Germany: MESA SYSTEMTECHNIK GMBH. Available at: www. mesa-systemtechnik.de. Accessed 1 December 2012. Miller, W. 2004. Potted flower bulbs popular in North America. Flower Tech 7(7):26-28. McCree, K. 1981. Photosynthetically active radiation. In Physiological Plant Ecology I, 41-55. Springer. Melbourne, B. A., and P. J. Daniel. 2003. A low-cost sensor for measuring spatiotemporal variation of light intensity on the streambed. Journal of the North American Benthological Society 22(1):143-151. Mellinger, D., M. Shomin, N. Michael, and V. Kumar. 2013. Cooperative grasping and transport using multiple quadrotors. In Distributed autonomous robotic systems, 545-558. Springer. Orozco, L. 2014. Optimizing Precision Photodiode Sensor Circuit Design. Analog Dialogue. Park, S., and J. How. 2004. Examples of Estimation Filters from Recent Aircraft Projects at MIT. Nov. Patel, P. N., M. A. Patel, R. M. Faldu, and Y. R. Dave. Quadcopter for Agricultural Surveillance. Pontailler, J.-Y. 1990. A cheap quantum sensor using a gallium arsenide photodiode. Functional Ecology:591-596. Sam, R., M. N. M. Tan, and M. S. Ismail. 2013. Quad-copter using ATmega328 microcontroller. In Electrical Machines and Systems (ICEMS), 2013 International Conference on. IEEE. Satler, M., M. Unetti, N. Giordani, C. A. Avizzano, and P. Tripicchio. 2014. Towards an autonomous flying robot for inspections in open and constrained spaces. In Multi-Conference on Systems, Signals Devices (SSD), 2014 11th International. IEEE. Stijger, H. 2004. All colours in light are equal for photosynthesis. Flower Tech 7(2):9-11. Taiz, L., and E. Zeiger. 2010. Plant physiology. Sunderland, MA: Sinauer Associates. Wang, H., S. Chen, L. Huang, and Y. Wang. 2006. Drop tester with orientation repeatability for electronic products. Experimental Techniques 30(6):31-36. Yang, I. C., K. W. Hsieh, C. Y. Tsai, Y. I. Huang, Y. L. Chen, and S. Chen. 2014. Development of an automation system for greenhouse seedling production management using radio-frequency-identification and local remote sensing techniques. Engineering in Agriculture, Environment and Food 7(1): 52-58. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/51808 | - |
dc.description.abstract | 近年來,精準農業 (Precision Agriculture) 技術倍受重視,除了應用於田間生產之外,也應用於溫室內的設施栽培。有許多相關溫室設施栽培及感測系統之研究陸續被提出,大部分研究之感測系統多使用有限數量的感測器,僅以其少量之量測數據代表整個環境資訊,此種作法會造成很大的誤差,對於分佈不均勻的環境影響更大。倘若以增加感測器數量來擴增量測的資訊,則會大幅增加系統的建置費用。 本研究以四軸飛行器搭載輕量級自製光量子感測器,研發可應用於溫室設施內進行特定位置作物管理 (Site Specific Crop Management) 之太陽光光度感測飛行機器人。本研究除進行設備研發外,還進行自製光量子感測器及整體飛行機器人之性能測試。以市售光量子感測器校正自製光量子感測器之結果,其Rc2值等於0.9967、SEC值為26.87 μmole/m2/s、RSEC值等於6.67%。另分析並比較動態飛行機器人與靜態感測器之量測結果,以評估使用動態飛行機器人之準確度,其標準誤差及相對標準誤差各為62.15μmole/m2/s、6.25%,產生誤差之原因,研判主要來自於空間的差異。 由實驗結果可結論,光度感測飛行機器人有別於傳統設施栽培使用之感測系統,能完整地呈現光資訊的分佈情形與不均勻性,並在建構成本與難易度上較使用移動機構之動態感測系統更為優秀,故在溫室之光資訊感測應用上,具有可行性。 | zh_TW |
dc.description.abstract | In recent years, the technique of Precision Agriculture (PA) has been highly focused. It was applied not only to the filed production but also to the greenhouses. Many research results about greenhouses and the sensing systems have been reported that current sensing systems in the greenhouses use a limited number of sensors to represent the information of the entire region. However, such sensing systems could cause information errors, even worse in non-uniform environments. The cost will be increased if more sensors are used to measure the non-uniform environments. A quantum-sensing flying robot has been developed in this study to realize the site specific crop management in greenhouses, which consists of a quadcopter and a light-weight quantum sensing module. The performances of the flying robot and quantum sensor carried by the flying robot were also evaluated. The results of customized quantum sensor made in this study being calibrated by commercial quantum sensor gave Rc2 value of 0.9967, SEC of 26.87μmole/m2/s, and RSEC of 6.67%. The comparison between flying robot with quantum sensing and static sensing system shows that the error mainly cause by spatial difference, and the standard error is 62.15μmole/m2/s with the relative standard error of 6.25%. The conclusions show that the flying robot with quantum sensing can used to sense the light spatial information in the greenhouses and show the non-uniform light distribution. On the comparison with the dynamic sensing system using moving carriers, the flying robot seems a better option in view of the construction cost and difficulty. Therefore, the flying robot with quantum sensing is feasible to apply to light spatial information sensing in greenhouses. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T13:50:54Z (GMT). No. of bitstreams: 1 ntu-104-R02631010-1.pdf: 6353876 bytes, checksum: 031d5e4c138ba24a3c713855e4cc3d97 (MD5) Previous issue date: 2015 | en |
dc.description.tableofcontents | 目 錄 誌 謝 i 摘 要. ii Abstract iii 目 錄 v 圖目錄 viii 表目錄 xii 第一章 前 言 1 1.1 前言 1 1.2 研究目的 3 第二章 文獻探討 4 2.1 精準農業 4 2.1.1 精準農業之設施栽培 6 2.1.2 精準農業之設施栽培感測系統 7 2.2 設施栽培光資訊 11 2.2.1 植物光合作用有效波段 13 2.2.2 光量子感測器 14 2.3四軸飛行器 16 2.3.1四軸飛行器的由來與現況 16 2.3.2四軸飛行器之建立 19 2.3.3四軸飛行器之應用 24 第三章 材料與方法 26 3.1 四軸飛行器系統 26 3.1.1 微型四軸飛行器 26 3.1.2 任務航巡時間推估 35 3.1.3自動化研究 42 3.2 光量子感測器之建立 48 3.2.1 光感材料選擇 48 3.2.2 系統設計 50 3.2.3 檢量模式建立與驗證 53 3.3 光度感測飛行機器人 62 3.3.1 系統整合 62 3.3.2 機器人感測效能測試 65 3.3.3 光資訊感測實驗 68 第四章 結果與討論 77 4.1 四軸飛行器系統 77 4.1.1 任務航巡時間推估 77 4.1.2 自動化研究成果 84 4.2 光量子感測器 93 4.2.1 檢量模式建立 93 4.2.2 檢量模式驗證 99 4.2.3 誤差探討 102 4.3 光度感測飛行機器人 104 4.3.1 光度感測飛行機器人建立 104 4.3.2 機器人感測效能測試 106 4.3.3 光場資訊分析比較 108 4.3.4 日累積光度資訊實驗 114 第五章 結論與建議 117 5.1 結論 117 5.2 建議事項與未來方向 118 5.2.1 光度感測飛行機器人之改良 118 5.2.2 自製光量子感測器改良 119 參考文獻 120 附錄一 124 附錄二 130 附錄三 132 附錄四 133 | |
dc.language.iso | zh-TW | |
dc.title | 溫室精準栽培之光度感測飛行機器人之研究 | zh_TW |
dc.title | The Study of Flying Robot with Quantum Sensing for Precision Cultivation in Greenhouses | en |
dc.type | Thesis | |
dc.date.schoolyear | 104-1 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 盛中德(Chung-Teh Sheng),陳加增(Chia-Tseng Chen),羅筱鳳(Hsiao-Feng Lo),顏炳郎(Ping-Lang Yen) | |
dc.subject.keyword | 精準農業,溫室,光量子感測器,四軸飛行器,飛行機器人, | zh_TW |
dc.subject.keyword | Precision Agriculture,Greenhouse,Quantum Sensor,Quadcopter,Flying Robot, | en |
dc.relation.page | 134 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2015-10-07 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物產業機電工程學研究所 | zh_TW |
顯示於系所單位: | 生物機電工程學系 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-104-1.pdf 目前未授權公開取用 | 6.2 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。