Obstacle avoidance transplanting method based on Kinect visual processing - Jin, Xin; Li, Ruoshi; Ji, Jiangtao; Yuan, Yanwei; Li, Mingyong (International Journal of Agricultural and Biological Engineering, 2021)
In modern facility agriculture, to improve the quality and efficiency of transplanting, the application of transplanting robots based on visual processing is becoming more and more widespread. In order to reduce the damage to plants during the transplanting process and reduce the damage rate of plant stems, leaves and substrates, a transplanting method based on Kinect visual processing combined with an inclined transplanting manipulator was proposed. In the research, the Kinect visual processing was used to obtain and process the seedling height information and leaf edge information, and the working coordinate system of the transplanting manipulator was established and applied to plan the obstacle avoidance path. Combined with the oblique manipulator, the obstacle avoidance transplanting method was proposed. Through the structural design and force analysis of the seedling transplanting device, the key parameters that affect the transplanting quality were obtained, and the optimal transplanting performance parameters were obtained through experiments. In the experiment, with the aid of the Kinect vision processing system, the designed obstacle avoidance transplanting manipulator had a leaf damage degree of 4.70%, a stem bending rate of 16.67%, substrate integrity of 83.45% and a transplanting quality parameter of 87.36%. The time for a single seedling transplanting was (8.32±0.40) s. The experiment result proves that the obstacle avoidance transplanting method based on Kinect visual processing can effectively reduce the damage to seedlings when ensuring the transplanting efficiency.Keywords: Kinect vision processing, oblique-type transplanting robot, path planning, obstacle avoidanceDOI: 10.25165/j.ijabe.20211405.6451Citation: Jin X, Li R S, Ji J T, Yuan Y W, Li M Y. Obstacle avoidance transplanting method based on Kinect visual processing. Int J Agric & Biol Eng, 2021; 14(5): 72–78.