Stereovision system for estimating tractors and agricultural machines transit area under orchards canopy

Abstract

Managing orchards requires delicate agricultural operations being typically carried out in narrow zones where the operators usually drive machineries under stress that could result in poor performance. In such conditions, the use of technology would help to manage the machines to reduce the hazardous work and eventual damage to the plants. To safely drive a tractor, the driver needs to be aware of its surroundings, thus a stereovision system can provide helpful information. Stereo imaging has proven to be an effective three-dimensional vision system. Indeed, the range (or third coordinate) information is useful to detect the obstacle distances. Such distances, when detected during agricultural operations, could be used to assist the operator in driving the tractor at regular or variable working speeds and eventually to provide manufacturers useful indications to model the form of ROPS (roll over protection structure). This study aimed to verify the closeness of agreement between manual and stereo-image measurements, and thus to provide helpful information regarding safety and working purposes. The system used a custom low-cost dual web-camera in combination with an image analysis algorithm in order to automatically extract the information needed. Manual independent measurements were carried out using a metric tape (sensitivity 1 cm). A regular structure was used for the analysis: four rows of ten trees each one. Alternated red and blue paper markers were placed on the hazelnut trees (two per tree) of two couples of rows for enhanced visibility. For each couple of trees (one on the right, the other on the left), the four markers formed a trapezoid that was measured. The results of the analysis demonstrated that the stereo vision provided distance measurements with reasonable accuracy (error <5%) in the range of distances lower than 20 m. The resolution assessed for the developed video system is suitable for obtaining distance information in real scenes. This information could be used to assist drivers to operate agricultural machineries through narrow tree rows during work execution. Moreover, such information could be used for safeguarding decision-making and/or for controlling some tractor functions such as continue moving, change driving direction, change 3-point hitch position, reduce transmission speed, halt the tractor. These functions will be necessary before tractors become fully autonomous. Finally, the measured distances, marking the narrow transitions between the tree rows, could be also used to study the ROPS form, both for working safely and for avoiding possible damage caused to the hazel trees laterally.