Acquiring Plant Features with Optical Sensing Devices in an Organic Strip-Cropping System

Abstract

The SUREVEG project focuses on improvement of biodiversity and soil fertility in organic agriculture through strip-cropping systems. To counter the additional workforce a robotic tool is proposed. Within the project, a modular proof of concept (POC) version will be produced that will combine detection technologies with actuation on a single-plant level in the form of a robotic arm. This article focuses on the detection of crop characteristics through point clouds obtained with two lidars. Segregation in soil and plants was successfully achieved without the use of additional data from other sensor types, by calculating weighted sums, resulting in a dynamically obtained threshold criterion. This method was able to extract the vegetation from the point cloud in strips with varying vegetation coverage and sizes. The resulting vegetation clouds were compared to drone imagery, to prove they perfectly matched all green areas in said image. By dividing the remaining clouds of overlapping plants by means of the nominal planting distance, the number of plants, their volumes, and thereby the expected yields per row could be determined.

Robotic Fertilisation Using Localisation Systems Based on Point Clouds in Strip-Cropping Fields

“…The data shown in Figure 6e correspond to a row of the plants in Figure 1 (the development before this work [43] that follows the same line of the Sureveg project). As a result, it shows the clustering assigned to each cloud of points, centers, defined edges and color assignment to identify each cluster.…”

“…Prior to the fertilisation stage, the robot and the sensors go over the crop row to take spatial and vegetative measurements of the plants. The obtained point clouds are processed offline to generate the general cloud of the entire crop row (G-PC), as detailed in [43]. The processed cloud is published in a ROS topic "/point_cloud_2".…”

“…As mentioned in Section 2.2, some plant parameters are required to define the fertiliser application zone, in which a semi-circular path can then be marked to apply the fertiliser. In [43], the removal of the soil points from the initial point cloud is discussed, leaving only the crop points. Based on this reduced cloud, the height (h), center (x, y), and plant boundaries are calculated.…”

“…Furthermore, this POC is also used to extract geometric characteristics of the plants as the basis for planning the robot's movements at the time of fertilisation, for which the robot arm must follow a path near the plant base to apply the treatment. The vegetative state and developmental status are determined as discussed in [43] resulting in a map of fertilisation prescriptions for the robot to carry out.…”

Trend Technologies for Robotic Fertilization Process in Row Crops

“…On the other hand, the main applications of laser-type sensors are reconstructing vegetative environments for their analysis using clustering techniques and point cloud processing. ( Krus et al, 2020 ; Mesas-Carrascosa et al, 2020 ; Cruz Ulloa et al, 2021 ; Schunck et al, 2021 ).…”