Path Planning for Autonomous Robotic Platform based on Created Sampling Maps

Abstract

Soil properties are of great importance in crop management, as they highly affect plant growth, crop production and product quality. In order to examine these properties, soil samples must be collected from the entire surface of the field. An effective soil sampling requires careful selection of the total number and the location of the samples. Therefore, soil properties can present heterogeneity along the field. For that reason, distributing sampling points evenly along the field is not considered as a best practice. In this research, in order to define the location of sampling points, the field was divided into homogenous management zones based on electrical conductivity (ECa) values. An equal number of points was distributed in each zone and a sampling map was created. Subsequently, a path for autonomous navigation was generated based on the created sampling map. More specifically, points of the map were distributed in the shortest possible distance order for the robotic platform to move while collecting the samples. In order to test the accuracy of the path planning, the proposed path was uploaded to the robotic platform and the movement was mapped. The path that was followed by the robotic platform was quite similar to the simulated path. The results of this research suggest that sensors such as a penetrometer can be mounted on an autonomous robotic platform in order to collect data from sampling points by moving along the created path. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)