請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84557完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭彥甫(Yan-Fu Kuo) | |
| dc.contributor.author | Yi-Hsin Yeh | en |
| dc.contributor.author | 葉逸新 | zh_TW |
| dc.date.accessioned | 2023-03-19T22:15:34Z | - |
| dc.date.copyright | 2022-09-26 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-09-20 | |
| dc.identifier.citation | Chang, C. L., Xie, B. X., & Wang, C. H. (2020). Visual guidance and egg collection scheme for a smart poultry robot for free-range farms. Sensors, 20(22), 6624. Council of Agriculture, Executive Yuan, Taiwan. (2012). Production cost and income analysis of major livestock and poultry products in Taiwan 2011. Taipei, Taiwan: Council of Agriculture, Executive Yuan. Council of Agriculture, Executive Yuan, Taiwan. (2021). Production cost and income analysis of major livestock and poultry products in Taiwan 2020. Taipei, Taiwan: Council of Agriculture, Executive Yuan. Council of Agriculture, Executive Yuan, Taiwan. (2022). Agricultural Statistics Yearbook 2021. Taipei, Taiwan: Council of Agriculture, Executive Yuan. Da Silva, B. M., Xavier, R. S., do Nascimento, T. P., & Gonçalves, L. M. (2017, November). Experimental evaluation of ROS compatible SLAM algorithms for RGB-D sensors. In 2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR) (pp. 1-6). IEEE. Demmers, T. G. M., Dennis, I. C., Norman, P., Butler, M., & Clare, D. RoboChick: An autonomous roving platform for data collection in poultry buildings, operational parameters and bird behaviour. PRECISION LIVESTOCK FARMING'19, 414. Grimstad, L., Zakaria, R., Le, T. D., & From, P. J. (2018, October). A novel autonomous robot for greenhouse applications. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 1-9). IEEE. Labbe, M., & Michaud, F. (2013). Appearance-based loop closure detection for online large-scale and long-term operation. IEEE Transactions on Robotics, 29(3), 734-745. Labbé, M., & Michaud, F. (2019). RTAB‐Map as an open‐source lidar and visual simultaneous localization and mapping library for large‐scale and long‐term online operation. Journal of Field Robotics, 36(2), 416-446. Lely Industries. (2014). Lely Discovery 90 S/SW. Retrieved from https://www.lely.com/solutions/housing-and-caring/discovery Liu, H. W., Chen, C. H., Tsai, Y. C., Hsieh, K. W., & Lin, H. T. (2021). Identifying images of dead chickens with a chicken removal system integrated with a deep learning algorithm. Sensors, 21(11), 3579. Marder-Eppstein, E. ROS Navigation Stack (2011). Git code. https://github.com/ros-planning/navigation Marin-Plaza, P., Hussein, A., Martin, D., & Escalera, A. D. L. (2018). Global and local path planning study in a ROS-based research platform for autonomous vehicles. Journal of Advanced Transportation, 2018. Octopus biosafety. (2019). Octopus Poultry Safe robot. Retrieved from https://octopusrobots.com/en/home Pomerleau, F., Colas, F., Siegwart, R., & Magnenat, S. (2013). Comparing ICP variants on real-world data sets. Autonomous Robots, 34(3), 133-148. Parajuli, P., Huang, Y., Tabler, T., Purswell, J. L., DuBien, J. L., & Zhao, Y. (2020). Comparative Evaluation of Poultry-Human and Poultry-Robot Avoidance Distances. Transactions of the ASABE, 63(2), 477-484. Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., ... & Ng, A. Y. (2009, May). ROS: an open-source Robot Operating System. In ICRA workshop on open source software (Vol. 3, No. 3.2, p. 5). Ragot, N., Khemmar, R., Pokala, A., Rossi, R., & Ertaud, J. Y. (2019, July). Benchmark of visual slam algorithms: Orb-slam2 vs rtab-map. In 2019 Eighth International Conference on Emerging Security Technologies (EST) (pp. 1-6). IEEE. Rösmann, C., Hoffmann, F., & Bertram, T. (2017). Online trajectory planning in ROS under kinodynamic constraints with timed-elastic-bands. In Robot Operating System (ROS) (pp. 231-261). Springer, Cham. Rösmann, C. Teb local planner package for ros (2017). Git code. http://wiki.ros.org/teb_local_planner. Stasewitsch, I., Schattenberg, J., & Frerichs, L. (2019, November). Cleaning Robot for Free Stall Dairy Barns: Sequential Control for Cleaning and Littering of Cubicles. In Iberian Robotics conference (pp. 115-126). Springer, Cham. Usher, C. T., Daley, W. D., Joffe, B. P., & Muni, A. (2017). Robotics for poultry house management. In 2017 ASABE annual international meeting (p. 1). American Society of Agricultural and Biological Engineers. Vroegindeweij, B. A., van Willigenburg, G. L., Koerkamp, P. W. G., & van Henten, E. J. (2014). Path planning for the autonomous collection of eggs on floors. Biosystems Engineering, 121, 186-199. Vroegindeweij, B. A., IJsselmuiden, J., & van Henten, E. J. (2016). Probabilistic localisation in repetitive environments: Estimating a robot’s position in an aviary poultry house. Computers and Electronics in Agriculture, 124, 303-317. Vroegindeweij, B. A., Blaauw, S. K., IJsselmuiden, J. M., & van Henten, E. J. (2018). Evaluation of the performance of PoultryBot, an autonomous mobile robotic platform for poultry houses. Biosystems engineering, 174, 295-315. Yao, L., Hu, D., Zhao, C., Yang, Z., & Zhang, Z. (2021). Wireless positioning and path tracking for a mobile platform in greenhouse. International Journal of Agricultural and Biological Engineering, 14(1), 216-223. Zheng, K. (2021). Ros navigation tuning guide. In Robot Operating System (ROS) (pp. 197-226). Springer, Cham. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84557 | - |
| dc.description.abstract | 在採用平飼法的商業雞舍中，養雞業者必須要經常的以人力進行徒步巡視，來監測雞隻的健康與環境狀態。然而對業者而言，這些巡視工作不僅費力更非常費時。因此，本研究的目標為開發一台可於商業雞舍中自主巡航且價格親民的機器人。有鑑於在臺灣商業雞舍的內部環境中，設備的配置大多較為密集。因此，機器人的體積被設計得緊湊小巧，以讓它能在狹窄的雞舍走道中穿梭。同時，機器人搭載了四輪驅動裝置和防塵外殼，使其可以順暢的在雞舍的米糠墊料上行駛。在軟體系統方面，本研究基於機器人作業系統（ROS）進行開發。機器人透過搭載的深度相機與光流里程計，運用同步定位與地圖構建（SLAM）和融合式定位兩種方法進行定位。由實驗結果顯示，同步定位與地圖構建和融合式定位在雞舍內的定位測試中分別僅有0.49和0.47公尺的平均絕對誤差，皆足以作為機器人在雞舍狹窄走道中的導航依據。為了讓機器人能自主巡航，機器人透過ROS navigation stack進行導航和障礙物迴避。本研究亦進行了一個實驗，藉此找出最適當的障礙物迴避參數值。透過實驗找出的最佳參數值，ROS navigation stack可以引導機器人在雞舍中順暢且有效率的行駛並避開障礙物。本研究所開發的機器人可以在商業雞舍中自主巡航，提供養雞業者一個自動化的巡視方案。 | zh_TW |
| dc.description.abstract | To manage a commercial floor rearing chicken farm, chicken farmers have to regularly patrol to observe chicken health and the environment conditions. However, the patrols are laborious and time-consuming. This study developed an affordable mobile robot that can autonomously cruise in commercial chicken farms. Considering the commercial chicken farms in Taiwan usually have narrow aisles between feed buckets, a compact robot was designed. The robot is equipped with a four-wheel drive module and a dust-proof case for driving on the litter in chicken farms. The system of the mobile robot was developed using robot operating system (ROS). Two localization approaches: simultaneous localization and mapping (SLAM) and fusion were utilized using a depth camera and an optical odometry as the sensors. Experiment results showed that the mean absolute errors of the SLAM and fusion were 0.49 m and 0.47 m, respectively, which comply with the requirements for navigating the robot in the narrow aisles of the chicken farm. The mobile robot performed navigation and obstacle avoidance using ROS navigation stack. An experiment was conducted to identify the appropriate values of ROS navigation stack parameters for obstacle avoidance. With the optimal parameters for the ROS navigation stack, the mobile robot avoided obstacles effectively and smoothly. The developed mobile robot can cruise in a commercial chicken farm autonomously, providing a solution to automate the regular patrols performed by chicken farmers. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T22:15:34Z (GMT). No. of bitstreams: 1 U0001-1309202214544300.pdf: 6989653 bytes, checksum: 04ab24cec30d42b0ff49d9461cf99ad2 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | ACKNOWLEDGEMENTS i 摘要 ii ABSTRACT iii TABLE OF CONTENTS iv LIST OF FIGURES vi LIST OF TABLES vii CHAPTER 1. INTRODUCTION 1 1.1 Background 1 1.2 Objectives 1 1.3 Organization 2 CHAPTER 2. LITERATURE REVIEW 3 2.1 Mobile robot applications for chicken farming 3 2.2 Localization approaches for agriculture mobile robot 3 CHAPTER 3. MATERIALS AND METHODS 5 3.1 Mobile robot 5 3.2 The system of the mobile robot 9 3.3 Mapping and localization 10 3.4 Navigation and obstacle avoidance configurations 11 3.5 Experimental site 12 3.6 Experiment design of localization and navigation 13 3.7 Experiment design of obstacle avoidance 14 CHAPTER 4. RESULTS AND DISCUSSION 17 4.1 Mapping result of SLAM 17 4.2 Performance of localization 17 4.3 Result of obstacle avoidance 19 CHAPTER 5. CONCLUSIONS 24 REFERENCES 25 | |
| dc.language.iso | en | |
| dc.subject | 深度相機 | zh_TW |
| dc.subject | 無人載具 | zh_TW |
| dc.subject | 雞 | zh_TW |
| dc.subject | 光流里程計 | zh_TW |
| dc.subject | 室內定位 | zh_TW |
| dc.subject | Chicken | en |
| dc.subject | Unmanned vehicle | en |
| dc.subject | Indoor positioning | en |
| dc.subject | Depth camera | en |
| dc.subject | Optical odometry | en |
| dc.title | 應用於商業雞舍之自主巡航機器人設計 | zh_TW |
| dc.title | Designing an Autonomous Cruising Robot in Commercial Chicken Farm | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 110-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 林達德(Ta-Te Lin),林顯易(Hsien-I Lin) | |
| dc.subject.keyword | 無人載具,室內定位,深度相機,光流里程計,雞, | zh_TW |
| dc.subject.keyword | Unmanned vehicle,Indoor positioning,Depth camera,Optical odometry,Chicken, | en |
| dc.relation.page | 28 | |
| dc.identifier.doi | 10.6342/NTU202203348 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2022-09-22 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 生物機電工程學系 | zh_TW |
| dc.date.embargo-lift | 2022-09-26 | - |
| 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 | |
|---|---|---|---|
| U0001-1309202214544300.pdf 授權僅限NTU校內IP使用（校園外請利用VPN校外連線服務） | 6.83 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。