Piggery robot monitoring system based on Kalman fusion algorithm

African swine fever has caused huge losses to the pig breeding industry, And the spread of African swine fever is diverse. In this study is aimed at the actual production needs of small and medium-sized pig farms, designed an unmanned piggery environment monitoring system with environmentaware robots as the main control was proposed to solve current backwardness of domestic piggery environmental monitoring equipment. In this study designs a track-suspended environment aware robot, and carried out finite element analysis and optimization of the environment-aware robot, finally, the maximum deformation of the mechanical structure is less than 2mm, and the natural frequency and the working frequency are not in the same range. Environment aware robot uses a multi-sensor Kalman filter fusion algorithm to detect the environmental parameters of the piggery, and perform actual verification of algorithm. The experimental results showed that under the environment of 25.6°C, the temperature data detection error is 0.19% when Kalman filter fusion algorithm is used, while the temperature data without algorithm error is 0.66%, which shows that the data detection error is reduced after using fusion algorithm, and the data reliability is improved to meet the accurate detection of environmental parameters in multiple areas of piggery. During the system test, the system operation is stable and can meet the actual demand, which can achieve the design purpose of saving labor cost, reducing environmental pollution and unmanned management.