Indoor Evaluation of Crop Rowand Grid Detection - System for an Automated Transplanter

If crops with considerable spacing can be arranged in a precise rectangular pattern, mechanical weeding can become an alternative to chemical methods by enabling treatment in two perpendicular directions. Realisation of such a pattern requires innovation of seedling transplanters. A computer vision-based sensing system was developed for detecting a transplanters posture relative to the crop. A method for indoor evaluation of the systems accuracy is proposed, using an experimental cart on a set of rails to control the vehicle’s posture. The method was successful in evaluating the estimates of the lateral offset and the heading angle, but the reliability of the validation values for the longitudinal distance is limited. Tests results showed that the maximum error on the measurements of the lateral offset is 1.5cm and that the standard deviation is smaller than 0.6cm. The maximum error on the angle measurements is 2.1◦. The standard deviation of the error is smaller than 0.65◦. The standard deviation of the error on the estimates of the longitudinal distance is typically 0.7cm.