Development of a Canopy Volume Reduction Technique for Easy Assessment and Harvesting of Valencia Citrus Fruits
B. S. Lee, U. A. Rosa
- 发表年份
- 2006
- 引用次数
- 21
摘要
The design and evaluation of a basic end-effector prototype for automated citrus harvesting was studied. The concept can be easily incorporated into the design of an automated or a robotic citrus harvester. The concept is based on a unique canopy volume reduction approach that takes advantage of the significant flexibility associated with citrus trees. The method provides a temporary reduction in the tree canopy volume, creating space for the action of simple and potentially fast three-axis Cartesian manipulators. The action of the device also creates fruit alignment that can simplify fruit quality assessment and picking. The prototype included a remotely controlled electro-pneumatic powered clipper to cut fruit stems, two remotely controlled pneumatic cylinders, and two hydraulic powered forks to reduce the canopy volume and to guide the cutting device to a specific location inside the tree canopy. The prototype performance was assessed by the quantification of its fruit removal success rate and damage to fruit and tree canopy. The fruit location of three Valencia orange trees was entirely mapped, and the device was operated on a forklift to evaluate its performance. Field trials were conducted in citrus groves located in Davis and Dinuba, California. This simple prototype end-effector successfully harvested an average of 84% of the fruit and caused no significant damage to harvested fruits during the harvest operations. The simple prototype end-effector, developed based on the canopy volume reduction technique, showed potential to reach significant citrus fruit removal. Based on these results, a future redesign of the system may improve the canopy penetration, increase successful removal rates, and maintain negligible fruit damage.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002