Dear Colleagues,

As the population ages and the level of agricultural labor reduces, agricultural production costs are also rising accordingly. Harvesting work with high labor intensity and low efficiency needs to be replaced by agricultural automation. As the reliability, continuity and stability of intelligent agricultural work steadily improves with the progress of research and gradually becomes superior to artificial work, the cost will gradually decrease. Robotics and automation in agriculture can help to mitigate labor shortages by reducing the reliance on manpower and can improve agricultural productivity to support sustainable economic development and growth. Robotic solutions have been studied by numerous researchers worldwide, including studies regarding low recognition and harvest rates and high damage rates for crops.

Smart farming represents the application of automation to agriculture, which is based on a precise and resource-efficient approach that attempts to sustainably achieve higher efficiency in agricultural goods production with increased quality. The benefits of precision agriculture involve increasing crop yields and quality while reducing the environmental impact. However, the marketability and adoption of agricultural automation in agriculture are currently limited by economic and technology barriers that prevent highly efficient autonomous operations at a cost that justifies the low commodity values. Recently, due to the improvement of the performance of agricultural robot systems and harvesting automation technology, they have been widely used in a variety of agricultural applications, including disease detection, crop monitoring, yield estimation and crop harvesting. Reacting technologies based on agricultural automation and robotics are separate but closely related sectors that cover the process of applying automatic control and robotic platforms at all levels of agricultural production.

In a harvesting robot system, because of the complexity of the operation environment, intelligent crop recognition and location are important. The mechanical structure directly determines the flexibility of robot movement and the complexity of control. In order to design a suitable harvesting robot, kinematics and dynamics analysis of the mechanism must be carried out; at the same time, optimization theory is used to design the robot structure. The open robot system has good expansibility, versatility and flexible operation ability. The establishment of an agricultural robot control system in line with the open definition and characteristics can ensure reliability and real-time control.

These challenges (and others) related to the application of harvest automation in agricultural robots and precision agriculture are expected to be covered in research and review manuscripts submitted to this Special Issue. The purpose of this Special Issue is to explore the various methods of crop yield harvesting, the adaptation of big data and the application of inter-seasonal databases from different platforms in crop yield harvesting. We invite studies focused on applications in harvesting methods, data fusion and the adaptation of big data to be submitted.

Dr. Baohua Zhang
Guest Editor

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• robotic harvesting
• agricultural robots
• sensing and control
• motion planning
• autonomous guidance
• robotic manipulator
• agricultural automation
• automated harvesting systems
• human-robot interaction
• multi-robot systems and collaboration operation