The advancement of agricultural technology has increasingly positioned robotic detection and localization techniques at the forefront, ensuring critical support for agricultural development through their accuracy and reliability. This paper provides an in-depth analysis of various methods used in detection and localization, including UWB, deep learning, SLAM, and multi-sensor fusion. In the domain of detection, the application of deep algorithms in assessing crop maturity and pest analysis is discussed. For localization, the accuracy of different methods in target positioning is examined. Additionally, the integration of convolutional neural networks and multi-sensor fusion with deep algorithms in agriculture is reviewed. The current methodologies effectively mitigate environmental interference, significantly enhancing the accuracy and reliability of agricultural robots. This study offers directional insights into the development of robotic detection and localization in agriculture, clarifying the future trajectory of this field and promoting the advancement of related technologies.

Fused deposition modeling and sintering (FDMS) is a novel 3D printing technique that combines fused deposition modeling with catalytic debinding and sintering processes to enable the rapid production of metal parts with low energy consumption and costs. Firstly, a 316L/POM composite filament is prepared. Subsequently, test specimens are printed using a fused deposition modeling (FDM) printer, followed by catalytic debinding and sintering processes to create dense metal parts. The process parameters show an influence on the part structure and, subsequently, the properties, and this study examines the microstructural characteristics of the 316L/POM composite filament at each process stage. Using tensile strength as the indicator, an orthogonal experiment is designed to identify suitable combinations of process parameters. Experimental results demonstrate that the FDMS process can manufacture 316L stainless steel parts; moreover, they influence the structure and, consequently, the mechanical behavior, as these are strongly related. By appropriately adjusting the process parameters, this method can be suitable for applications requiring functional parts with less stringent strength requirements.