The goal of this research is to improve the modern process of counting individual trees in a nursery, which at the moment is inefficient, costly, and inaccurate. Multiple times a year, employees must walk down every row in a tree nursery and count each tree in order to have an estimate of the nurseries stock. This tedious and time consuming job could be replaced by an autonomous rover, creating the opportunity to save time and money, as well as to both get a more accurate estimate of the number of trees and to record the diameters of the different trees.
Our research project designs, builds, programs, and tests an autonomous rover that can be placed in a tree nursery and successfully navigate through each row. Although this has been done before by other universities and companies, such systems run $50,000 or more. We currently are operating under a total budget of a $1,000.
In order to stay under budget we decided to create a low-cost LIDAR system to accurately estimate the position of the trees in relation to the robot. This custom LIDAR system maps the surrounding unknown environment and plots each data point. We then use various algorithms to cluster the data into 4 points, 2 points on each row. These points are used to create lines that symbolize the left and right rows of trees. The rover then determines its position in the row and calculates the movement needed to drive down the middle of the row.
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