Autonomous agricultural robot – Testing of the vision system for plants/weed classification

Abstract

The aim of the paper was to present results of the vision system for plants/weeds classification testing of autonomous robot for sowing and wide row planting. Autonomous work of the robot in range of traction and agronomic processes will be implemented on the basis of data from a many sensors (cameras, position and distance). Positive test results will allow for the use of the robot in organic crops requiring mechanical removal of weeds or in crops with application of selective liquid agrochemicals limited to the minimum. Unless the control systems are improved and development costs are compensated, the production of autonomous agricultural systems will increase. So that very important is mentioned in this paper, vision system of plant/weed classification. The vision system for sugar beet/weed and sweet corn/weed classification was build and tested. The position of each plant must be determined for intra-row weeding. This means that plants have to be classified into two classes, i.e., sugar beet (sweet corn) or weed.