Research and Development for the Hurdle Avoidance During Transplanting Manipulation Based on Kinect Vision Processing

Abstract

To avoid damage to plants during the transplanting process, a transplanting method based on the combination of the Kinect machine visual system and the low-damage transplanting end effector was proposed to reduce the damage to the stems and leaves from transplanting end effectors during the transplanting process. The inclined manipulator was designed can avoid the characteristics of the seedling itself during the transplanting process to avoid obstacles. Under the experimental condition, the oblique transplanting manipulator assisted by the Kinect vision processing system achieved 4.70% leaf damage, 16.70% stem bending, 83.45% substrate integrity, and the transplanting quality parameters were 87.36%. The completion time of a single transplant was 8.32±0.4 s, the results proved that the low-damage transplanting manipulator based on the machine vision system can effectively reduce the damage rate of the stems and leaves. This obstacle avoidance transplant method can be extended to seedlings planted in 50 plugs. Research and development for hurdle avoidance during transplanting manipulation based on Kinect vision processing can provide theoretical support for future obstacle avoidance transplantation.

Digital Twins in Plant Factory: A Five-Dimensional Modeling Method for Plant Factory Transplanter Digital Twins

“…Improper use could cause damage and death to plants, while also increasing labor costs and production risks [4,5]. Plant transplantation is a vital link in the production process of plant factories [6][7][8], thus it is crucial to establish a transplanting machine model suitable for the operating environment of plant factories in order to optimize costs and increase efficiency in the planting process.…”