Planar double-jointed robot is a kind of widely used robot. In the past decades, with the development of science and technology, planar double-jointed robot has a great breakthrough in many aspects, especially in the actual camera and attitude analysis. In recent years, pun-section manipulator has made great progress in technology, but its kinematic characteristics and the human body’s ability to move have a great gap. So, in the moving plane, we need to study how to improve its camera ability to find a more stable and effective camera mode, and to a certain extent, to meet its requirements in complex working conditions. Simulating the pose of two joints, we seek a more stable and effective camera mode to improve its moving speed, expand its moving space, and lay a solid foundation for its application. Planar double-jointed robot is the most representative one at present. It includes machinery, material, electronics, computer, sensor, drive, intelligent control, artificial intelligence, and so on. Because it is closer to the human body, more suitable for people’s work and work, so it does not need to change its environment, so it is regarded as having a high affinity for people’s machinery. Its characteristic is that it has the good adaptability and the flexibility, but the double joint camera’s support discontinuity enables it to be able to adapt each kind of complex situation well. It can not only climb the stairs but also in the messy ground smooth through and also in the inconvenient passage through. The aim of this paper is to analyze the unique advantages and irreplaceable characteristics of the planar double-jointed robot based on the bionic and mechanical research results. This paper analyzes the mechanical technology by means of literature review and actual data analysis. The experimental results show that the biggest difference between the two articulated robots and other robots is that they have two human-like joint motions.

Aiming at the problems of low precision, strong subjectivity, and continuous measurement in the current measurement methods of corn phenotypic traits, a method of measuring corn phenotypic traits with high precision, low cost, easy carrying and continuous measurement was proposed. Firstly, the three-dimensional scanning device Kinect 2.0 is used to collect corn information and process and reconstruct the collected point cloud. Then, the stem and leaf point clouds were segmented by straight-through filtering, ellipse fitting and region growth segmentation. Finally, the phenotypic parameters of corn were obtained by triangulation and plane fitting for the segmented corn leaves, and the accuracy was analyzed. The results showed that the accuracy of corn plant height was 97.622 %, the average relative error of stem long axis was 9.46 %, the average relative error of stem short axis was 11.17 %, and the accuracy of leaf area was 95.577 %. Studies have shown that this method provides a new method for continuous measurement of phenotypic traits in corn.

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