| Autor: |
Lehnert, Chris, English, Andrew, McCool, Chris, Tow, Adam, Perez, Tristan |
| Rok vydání: |
2017 |
| Předmět: |
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| Zdroj: |
IEEE Robotics and Automation Letters, vol. 2, no. 2, pp. 872-879, April 2017. doi: 10.1109/LRA.2017.2655622 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1109/LRA.2017.2655622 |
| Popis: |
In this letter, we present a new robotic harvester (Harvey) that can autonomously harvest sweet pepper in protected cropping environments. Our approach combines effective vision algorithms with a novel end-effector design to enable successful harvesting of sweet peppers. Initial field trials in protected cropping environments, with two cultivar, demonstrate the efficacy of this approach achieving a 46% success rate for unmodified crop, and 58% for modified crop. Furthermore, for the more favourable cultivar we were also able to detach 90% of sweet peppers, indicating that improvements in the grasping success rate would result in greatly improved harvesting performance. |
| Databáze: |
arXiv |
| Externí odkaz: |
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