In the process of transition from agricultural society to industrial society,which started with the Industrial Revolution in England,the mechanization process experienced five different stages and in the last stage,wi...In the process of transition from agricultural society to industrial society,which started with the Industrial Revolution in England,the mechanization process experienced five different stages and in the last stage,with the development of computers,automation in production was achieved.While developments in a certain region or country of the world spread to other parts of the world with technological spread,technological revolutions also spread and paradigm changes occurred.With the development of information processing technologies,productivity has started to increase with the use of automation and robot technology in production.This process,which continued until the 2010s,is thought to lead to the formation of smart factories that can produce under the dominance of robots,after the new point reached in artificial intelligence and robot technology,and this development will further increase productivity in production.Intelligent robots working in the internet of things system will be able to work with greater power and longer periods than humans,and smart factories that are almost never shut down will emerge.In the transformation in this process,which is also called robonomics,changes in the theory of economy may occur and a new economic order may emerge.The question of why behind-the-scenes countries,such as Turkey,could not catch up with the leading ones,is another matter of discussion.However,in such periods of technological paradigm change,an opportunity arises for lagging countries for their economic development.On the other hand,we can say that Turkey will either be able to catch up with the technological level of developed countries by taking advantage of the opportunity,by means of a step-by-step technological development,or it will continue to stay among the countries that lag behind by missing the opportunity.展开更多
As the agricultural internet of things(IoT)technology has evolved,smart agricultural robots needs to have both flexibility and adaptability when moving in complex field environments.In this paper,we propose the concep...As the agricultural internet of things(IoT)technology has evolved,smart agricultural robots needs to have both flexibility and adaptability when moving in complex field environments.In this paper,we propose the concept of a vision-based navigation system for the agricultural IoT and a binocular vision navigation algorithm for smart agricultural robots,which can fuse the edge contour and the height information of rows of crop in images to extract the navigation parameters.First,the speeded-up robust feature(SURF)extracting and matching algorithm is used to obtain featuring point pairs from the green crop row images observed by the binocular parallel vision system.Then the confidence density image is constructed by integrating the enhanced elevation image and the corresponding binarized crop row image,where the edge contour and the height information of crop row are fused to extract the navigation parameters(θ,d)based on the model of a smart agricultural robot.Finally,the five navigation network instruction sets are designed based on the navigation angleθand the lateral distance d,which represent the basic movements for a certain type of smart agricultural robot working in a field.Simulated experimental results in the laboratory show that the algorithm proposed in this study is effective with small turning errors and low standard deviations,and can provide a valuable reference for the further practical application of binocular vision navigation systems in smart agricultural robots in the agricultural IoT system.展开更多
In the smart warehousing system adopting cargo-to-person mode, all the items are stored in the movable shelves. There are some warehouse robots transporting the shelves to the working platforms for completing order pi...In the smart warehousing system adopting cargo-to-person mode, all the items are stored in the movable shelves. There are some warehouse robots transporting the shelves to the working platforms for completing order picking or items replenishment tasks. When the number of robots is insufficient, the task allocation problem of robots is an important issue in designing the warehousing system. In this paper, the task allocation problem of insufficient warehouse robots (TAPIR) is investigated. Firstly, the TAPIR problem is decomposed into three sub-problems: task grouping problem, task scheduling problem and task balanced allocation problem. Then three sub-problems are respectively formulated into integer programming models, and the corresponding heuristic algorithms for solving three sub-problems are designed. Finally, the simulation and analysis are done on the real data of online bookstore. Simulation results show that the mathematical models and algorithms of this paper can provide a theoretical basis for solving the TAPIR problem.展开更多
文摘In the process of transition from agricultural society to industrial society,which started with the Industrial Revolution in England,the mechanization process experienced five different stages and in the last stage,with the development of computers,automation in production was achieved.While developments in a certain region or country of the world spread to other parts of the world with technological spread,technological revolutions also spread and paradigm changes occurred.With the development of information processing technologies,productivity has started to increase with the use of automation and robot technology in production.This process,which continued until the 2010s,is thought to lead to the formation of smart factories that can produce under the dominance of robots,after the new point reached in artificial intelligence and robot technology,and this development will further increase productivity in production.Intelligent robots working in the internet of things system will be able to work with greater power and longer periods than humans,and smart factories that are almost never shut down will emerge.In the transformation in this process,which is also called robonomics,changes in the theory of economy may occur and a new economic order may emerge.The question of why behind-the-scenes countries,such as Turkey,could not catch up with the leading ones,is another matter of discussion.However,in such periods of technological paradigm change,an opportunity arises for lagging countries for their economic development.On the other hand,we can say that Turkey will either be able to catch up with the technological level of developed countries by taking advantage of the opportunity,by means of a step-by-step technological development,or it will continue to stay among the countries that lag behind by missing the opportunity.
基金the National Natural Science Foundationof China(No.31760345).
文摘As the agricultural internet of things(IoT)technology has evolved,smart agricultural robots needs to have both flexibility and adaptability when moving in complex field environments.In this paper,we propose the concept of a vision-based navigation system for the agricultural IoT and a binocular vision navigation algorithm for smart agricultural robots,which can fuse the edge contour and the height information of rows of crop in images to extract the navigation parameters.First,the speeded-up robust feature(SURF)extracting and matching algorithm is used to obtain featuring point pairs from the green crop row images observed by the binocular parallel vision system.Then the confidence density image is constructed by integrating the enhanced elevation image and the corresponding binarized crop row image,where the edge contour and the height information of crop row are fused to extract the navigation parameters(θ,d)based on the model of a smart agricultural robot.Finally,the five navigation network instruction sets are designed based on the navigation angleθand the lateral distance d,which represent the basic movements for a certain type of smart agricultural robot working in a field.Simulated experimental results in the laboratory show that the algorithm proposed in this study is effective with small turning errors and low standard deviations,and can provide a valuable reference for the further practical application of binocular vision navigation systems in smart agricultural robots in the agricultural IoT system.
基金Project Supported： National Natural Science Foundation of China （11131009, 71540028, F012408）, Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality （CIT＆TCD20130327）, and major research project of Beijing Wuzi University.
文摘In the smart warehousing system adopting cargo-to-person mode, all the items are stored in the movable shelves. There are some warehouse robots transporting the shelves to the working platforms for completing order picking or items replenishment tasks. When the number of robots is insufficient, the task allocation problem of robots is an important issue in designing the warehousing system. In this paper, the task allocation problem of insufficient warehouse robots (TAPIR) is investigated. Firstly, the TAPIR problem is decomposed into three sub-problems: task grouping problem, task scheduling problem and task balanced allocation problem. Then three sub-problems are respectively formulated into integer programming models, and the corresponding heuristic algorithms for solving three sub-problems are designed. Finally, the simulation and analysis are done on the real data of online bookstore. Simulation results show that the mathematical models and algorithms of this paper can provide a theoretical basis for solving the TAPIR problem.
