In recent years, autonomous robots have been gradually introduced into various agricultural operations such as disease detection, harvesting, and weed removal to address the ever-increasing labor shortage problem and increase growers' profit. Accurate navigation from one row to another is one of the many challenging tasks for an autonomous robot that is scouting in semi-structured agricultural fields. In this study, a marker-based row alignment control is proposed for the cross-bed motion of a scouting robot in strawberry fields. Specifically, a feature-based computer vision algorithm is used to detect primitive markers placed at the end of each planting bed. Then the image coordinates of detected markers are used to guide the robot to move away from one row and then align with the next one.  The algorithm will automatically adjust the exposure settings of the camera, avoiding repetitive calibrations under different weather conditions. The proposed method is low cost and robust with respect to varying lighting conditions by using a scene invariant color ratio index. The algorithm has been successfully validated in a local strawberry farm.


Marker Based Row Alignment Control for an Agricultural Scouting Robot

Division / Sponsors: 
Dynamic Systems & Control (DSCD)

Paper Proceedings: https://asmedigitalcollection.asme.org/DSCC/DSCC2020/volume/84270

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