Xin Zhao, Wanli Wang, Long Wen, Zhibo Chen, Sixian Wu, Kun Zhou, Mengyao Sun, Lanjun Xu, Bingbing Hu, Caicong Wu
{"title":"智能农业中的数字孪生:用于自动农业车辆的基于汽车的模拟器","authors":"Xin Zhao, Wanli Wang, Long Wen, Zhibo Chen, Sixian Wu, Kun Zhou, Mengyao Sun, Lanjun Xu, Bingbing Hu, Caicong Wu","doi":"10.25165/j.ijabe.20231604.8039","DOIUrl":null,"url":null,"abstract":"Digital twins can improve the level of control over physical entities and help manage complex systems by integrating a range of technologies. The autonomous agricultural machine has shown revolutionary effects on labor reduction and utilization rate in field works. Autonomous vehicles in precision agriculture have the potential to improve competitiveness compared to current crop production methods and have become a research hotspot. However, the development time and resources required in experiments have limited the research in this area. Simulation tools in unmanned farming that are required to enable more efficient, reliable, and safe autonomy are increasingly demanding. Inspired by the recent development of an open-source virtual simulation platform, this study proposed an autoware-based simulator to evaluate the performance of agricultural machine guidance based on digital twins. Oblique photogrammetry using drones is used to construct three-dimensional maps of fields at the same scale as reality. A communication format suitable for agricultural machines was developed for data input and output, along with an inter-node communication methodology. The conversion, publishing, and maintenance of multiple coordinate systems were completed based on ROS (Robot Operating System). Coverage path planning was performed using hybrid curves based on Bézier curves, and it was tested in both a simulation environment and actual fields with the aid of Pure Pursuit algorithms and PID controllers. Keywords: autoware, simulation platform, autonomous agricultural vehicle, digital twin; autonomous robots DOI: 10.25165/j.ijabe.20231604.8039 Citation: Zhao X, Wang W L, Wen L, Chen Z B, Wu S X, Zhou K, et al. Digital twins in smart farming: An autoware-based simulator for autonomous agricultural vehicles. Int J Agric & Biol Eng, 2023; 16(4): 185-190.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Digital twins in smart farming: An autoware-based simulator for autonomous agricultural vehicles\",\"authors\":\"Xin Zhao, Wanli Wang, Long Wen, Zhibo Chen, Sixian Wu, Kun Zhou, Mengyao Sun, Lanjun Xu, Bingbing Hu, Caicong Wu\",\"doi\":\"10.25165/j.ijabe.20231604.8039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Digital twins can improve the level of control over physical entities and help manage complex systems by integrating a range of technologies. The autonomous agricultural machine has shown revolutionary effects on labor reduction and utilization rate in field works. Autonomous vehicles in precision agriculture have the potential to improve competitiveness compared to current crop production methods and have become a research hotspot. However, the development time and resources required in experiments have limited the research in this area. Simulation tools in unmanned farming that are required to enable more efficient, reliable, and safe autonomy are increasingly demanding. Inspired by the recent development of an open-source virtual simulation platform, this study proposed an autoware-based simulator to evaluate the performance of agricultural machine guidance based on digital twins. Oblique photogrammetry using drones is used to construct three-dimensional maps of fields at the same scale as reality. A communication format suitable for agricultural machines was developed for data input and output, along with an inter-node communication methodology. The conversion, publishing, and maintenance of multiple coordinate systems were completed based on ROS (Robot Operating System). Coverage path planning was performed using hybrid curves based on Bézier curves, and it was tested in both a simulation environment and actual fields with the aid of Pure Pursuit algorithms and PID controllers. Keywords: autoware, simulation platform, autonomous agricultural vehicle, digital twin; autonomous robots DOI: 10.25165/j.ijabe.20231604.8039 Citation: Zhao X, Wang W L, Wen L, Chen Z B, Wu S X, Zhou K, et al. Digital twins in smart farming: An autoware-based simulator for autonomous agricultural vehicles. 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Digital twins in smart farming: An autoware-based simulator for autonomous agricultural vehicles
Digital twins can improve the level of control over physical entities and help manage complex systems by integrating a range of technologies. The autonomous agricultural machine has shown revolutionary effects on labor reduction and utilization rate in field works. Autonomous vehicles in precision agriculture have the potential to improve competitiveness compared to current crop production methods and have become a research hotspot. However, the development time and resources required in experiments have limited the research in this area. Simulation tools in unmanned farming that are required to enable more efficient, reliable, and safe autonomy are increasingly demanding. Inspired by the recent development of an open-source virtual simulation platform, this study proposed an autoware-based simulator to evaluate the performance of agricultural machine guidance based on digital twins. Oblique photogrammetry using drones is used to construct three-dimensional maps of fields at the same scale as reality. A communication format suitable for agricultural machines was developed for data input and output, along with an inter-node communication methodology. The conversion, publishing, and maintenance of multiple coordinate systems were completed based on ROS (Robot Operating System). Coverage path planning was performed using hybrid curves based on Bézier curves, and it was tested in both a simulation environment and actual fields with the aid of Pure Pursuit algorithms and PID controllers. Keywords: autoware, simulation platform, autonomous agricultural vehicle, digital twin; autonomous robots DOI: 10.25165/j.ijabe.20231604.8039 Citation: Zhao X, Wang W L, Wen L, Chen Z B, Wu S X, Zhou K, et al. Digital twins in smart farming: An autoware-based simulator for autonomous agricultural vehicles. Int J Agric & Biol Eng, 2023; 16(4): 185-190.
期刊介绍:
International Journal of Agricultural and Biological Engineering (IJABE, https://www.ijabe.org) is a peer reviewed open access international journal. IJABE, started in 2008, is a joint publication co-sponsored by US-based Association of Agricultural, Biological and Food Engineers (AOCABFE) and China-based Chinese Society of Agricultural Engineering (CSAE). The ISSN 1934-6344 and eISSN 1934-6352 numbers for both print and online IJABE have been registered in US. Now, Int. J. Agric. & Biol. Eng (IJABE) is published in both online and print version by Chinese Academy of Agricultural Engineering.