A team from Virginia Polytechnic Institute and State University (Virginia Tech) received first prize in the third annual 2018 agBOT Challenge in Indiana.
Their task was to build an autonomous system for locating, identifying, sorting, and harvesting ripe watermelons in a field.
The Virginia Tech group included a mechanical engineering senior design team to design and build such a harvester, and a special studies team to create an autonomous vehicle to tow the harvester.
The group incorporated computer vision and machine learning into the tow vehicle so it could locate watermelons; if melons were not in sight, the vehicle employed way-point navigation to navigate the fields.
Upon spotting a melon, the machine's cameras guided it toward the target, and then the harvester determined ripeness by slapping the fruit and listening for a hollow sound via a microphone and audio analysis. Watermelons that satisfied the frequency indicating ripeness were scooped into a storage unit.
From Augusta Free Press
View Full Article
Abstracts Copyright © 2018 Information Inc., Bethesda, Maryland, USA
No entries found