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Overview of Sensor Technologies Used for 3D Localization of Asparagus Spears for Robotic Harvesting

机译：用于芦笋矛头进行机器人收获的3D定位的传感器技术概述

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Advances in agricultural automation, coupled with a general decline of available labour has generated interest in automated harvesting of various crops. Paramount to the success of such systems is the development of accurate, robust detection technologies and localization strategies. This paper presents an overview of sensor technologies used in the detection and localization of green asparagus spears for robotic harvesting. Tactile, photoelectric, machine vision and time-of-flight sensors are investigated and their applicability for use in robotic asparagus harvesting is evaluated. Investigation of previous asparagus harvesting devices has revealed that no such device has yet achieved commercial viability. It was identified that this is likely due to weaknesses in currently employed detection technologies, namely slow response times, high sensitivity to changes in ambient lighting conditions and requirement for frequent manual calibration. Of the sensor technologies investigated it was found that time-of-flight cameras, such as the Microsoft Kinect V2 are the most feasible for the detection of asparagus spears for robotic harvesting. It was concluded that further research would be conducted into the application of such sensors into a commercially viable harvester.
机译：农业自动化的进步，加上可用劳动力的普遍减少，引起了人们对各种作物自动收获的兴趣。此类系统成功的关键是开发准确，强大的检测技术和定位策略。本文概述了用于机器人收获的绿色芦笋矛的检测和定位中使用的传感器技术。研究了触觉，光电，机器视觉和飞行时间传感器，并评估了它们在机器人芦笋收获中的适用性。对先前的芦笋收获设备的研究表明，尚无此类设备具有商业可行性。已经确定，这可能是由于当前采用的检测技术的弱点，即响应时间慢，对环境光照条件变化的高度敏感性以及频繁手动校准的要求。在所研究的传感器技术中，发现飞行时间相机（例如Microsoft Kinect V2）最适合用于机器人收获的芦笋矛头检测。结论是，将对将这种传感器应用于商业上可行的收割机进行进一步的研究。

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