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Featured Application: Proof-of-concept versions of mixed-reality applications for controlling and monitoring a digital twin-based roadheader with timeliness, accuracy, and reliability, and the general architecture of a mixed-reality digital twin monitoring system for a roadheader is constructed. The working environment of the coal mine boom-type roadheader is harsh with large blind areas and numerous safety hazards for operators. Traditional on-site or remote control methods do not meet the requirements for intelligent tunneling. This paper proposes a digital twin monitoring system of an EBZ-type roadheader based on mixed reality (MR). First, the system integrates a five-dimensional digital twin model to establish the boom-type roadheader digital twin monitoring system. Second, the Unity3D software (v2020.3.25f1c1) and the MR Hololens (v22621.1133 produced by Microsoft) are used to build a digital twin human–machine interaction platform, achieving bidirectional mapping and driving of cutting operation data. Third, a twin data exchange program is designed by employing the Winform framework and the C/S communication architecture, making use of the socket communication protocol to transmit and store the cutting model data within the system. Finally, a physical prototype of the boom-type roadheader is built, and a validation experiment of the monitoring system's digital twin is conducted. The experimental results show that the average transmission error of the cutting model data of the twin monitoring system is below 0.757%, and the execution accuracy error is below 3.7%. This system can achieve bidirectional real-time mapping and control between the twins, which provides a new monitoring method for actual underground roadheader operations. It effectively eliminates the operator's blind areas and improves the intelligence level of roadheader monitoring. Beyond mining, this methodology can be extended to the monitoring and control of other mining equipment, predictive maintenance in manufacturing, and infrastructure management in smart cities. [ABSTRACT FROM AUTHOR]

The development of intelligent fruit harvesting robots is important in improving agricultural production. In this paper, we initiated the R&D of a mechanical end-effector for fruit harvesting on the basis of the intelligence of agricultural robots. First, we provided a detailed description of the hardware components and software control of the mechanical end-effector, analyzed the mechanism of servo controlling and established a mathematical modeling of the mechanical end-effector junctions by analyzing the harvesting movement. Thereafter, the coordinates of the target fruits are disassembled and analyzed in the context of the mathematical model for precise locating and harvesting. Finally, a trail experiment of harvesting kiwifruit was conducted. The outcome implies that each module in the harvesting robot system functions well. The proposed mathematical modeling method and servo control can provide accurate harvesting movements to the mechanical end-effector. [ABSTRACT FROM AUTHOR]

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By analyzing the current situation of experimental platforms based on the Internet of Things (IOT) and the cultivation of talents, we established the talents' cultivating orientation and an experiment platform for innovation. In accordance with the requirements of a practical and creative curriculum, a method of modularization was adopted to design a platform. With this, the platform can basically satisfy the needs of varying teaching experiments, which can increase the opportunities for students' comprehensive application. The platform has been widely used in experimental and practice teaching in the past three years, such as in synthetic experiments, graduate programs, and practice projects at Zhongkai University of Agriculture and Engineering, Guilin University of Technology, etc. Results show that the innovative experimental platform has broad application prospects and effectiveness to meet the requirements of students' in-depth learning and research of IOT technologies. The platform expanded the students' basic understanding of IOT and improved their innovation. [ABSTRACT FROM AUTHOR]

The development of intelligent fruit harvesting robots is important in improving agricultural production. In this paper, we initiated the R&D of a mechanical end-effector for fruit harvesting on the basis of the intelligence of agricultural robots. First, we provided a detailed description of the hardware components and software control of the mechanical end-effector, analyzed the mechanism of servo controlling and established a mathematical modelling of the mechanical end-effector junctions by analyzing the harvesting movement. Thereafter, the coordinates of the target fruits are disassembled and analyzed in the context of the mathematical model for precise locating and harvesting. Finally, a trail experiment of harvesting kiwifruit was conducted. The outcome implies that each module in the harvesting robot system functions well. The proposed mathematical modelling method and servo control can provide accurate harvesting movements to the mechanical end-effector. [ABSTRACT FROM AUTHOR]

Intelligent agricultural machinery is a key component in developing precise and intellectual agriculture. However, achieving the accurate operation of intellectual agricultural equipment depends on precisely sensing the field position. This study adopts built-in technology and integrates wireless communication and Global Positioning System (GPS) stand-alone positioning to obtain low-cost and high-precision positioning in production. Information collection and transmission by the low-cost agricultural machinery are realized to implement overall management, monitoring, and scheduling. Test results show that the measured and actual errors can be stabilized to less than 3%, and the accurate position of an agricultural vehicle can be obtained. The system exhibits good expandability, functional implementation, and stable performance. It is significantly useful in engineering applications. [ABSTRACT FROM AUTHOR]