  Following a global trend, the lack of reliable access to skilled labour is
causing critical issues for the effective management of apple orchards. One of
the primary challenges is maintaining skilled human operators capable of making
precise fruitlet thinning decisions. Thinning requires accurately measuring the
true crop load for individual apple trees to provide optimal thinning decisions
on an individual basis. A challenging task due to the dense foliage obscuring
the fruitlets within the tree structure. This paper presents the initial
design, implementation, and evaluation details of the vision system for an
automatic apple fruitlet thinning robot to meet this need. The platform
consists of a UR5 robotic arm and stereo cameras which enable it to look around
the leaves to map the precise number and size of the fruitlets on the apple
branches. We show that this platform can measure the fruitlet load on the apple
tree to with 84% accuracy in a real-world commercial apple orchard while being
87% precise.
