Evaluating object detection and stereoscopic localization of a robotic cotton harvester under real field conditions

Hussein Gharakhani; J. Alex Thomasson

doi:10.1117/12.2666389

13 June 2023 Evaluating object detection and stereoscopic localization of a robotic cotton harvester under real field conditions

Hussein Gharakhani, J. Alex Thomasson

Author Affiliations +

Proceedings Volume 12539, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VIII; 125390B (2023) https://doi.org/10.1117/12.2666389
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Perception plays a significant role in agricultural robots. If a robot fails to detect a target in the perception step, it will not perform any actions towards that target even if the control and manipulation systems are very effective. A robotic cotton harvester was tested in the field to evaluate its perception system performance. A ZED 2i stereo camera in conjunction with YOLOv4-tiny was utilized to detect and localize cotton bolls. To train the object detection network image data was gathered in two steps. Adding a black background panel behind the target row in the second step of image gathering eliminated the cotton bolls from other rows in the image. It also helped to improve object detection performance. The robot could detect 78% of the cotton bolls on the plant and localized 70% of the detected bolls. Assessing the precision of the localization system showed that, the mean absolute error on the X, Y, and Z axes in the camera’s coordinate system was 5.8, 5.2, and 8.1 mm respectively.

Conference Presentation

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Hussein Gharakhani and J. Alex Thomasson "Evaluating object detection and stereoscopic localization of a robotic cotton harvester under real field conditions", Proc. SPIE 12539, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VIII, 125390B (13 June 2023); https://doi.org/10.1117/12.2666389

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