Machine Vision Assisted Robotic Seedling Transplanting

Abstract

A machine vision assisted robotic transplanter was developed to improve the quality of the grow-out trays that contain transplanted plugs. The machine vision system was designed to identify and locate empty positions in the transplanted seedling trays. The detection algorithm was able to inspect uneven height growth medium blocks in randomly oriented seedling trays. Fifteen species of seedlings were used in evaluating the integrated machine vision assisted robotic system. The overall vision system success rate in identifying mistransplanted empty growth medium blocks in the transplanted seedling trays is 95%.