Agriculture Reference
In-Depth Information
impede efficient robotic harvesting: (1) locating fruit occluded by the leaf canopy and
(2) harvesting fruit located in the tree or plant interior. In both cases, a plant system
that presented the majority of the fruit at the canopy surface would improve harvest-
ability. There are two possible solutions. The first would suggest a thin leaf canopy so
that the detection systems could more easily view the plant interior, and the second
suggests a dense canopy that might force more fruit to grow at the surface. The two
strategies seem to be in conflict under normal tree behavior. Sparsely leafed trees
tend to have more interior fruit, which reduces fruit accessibility, whereas densely
leafed trees will be more difficult to sense the interior fruit. A tree that naturally
fruited at the limb extremities with minimal interior fruit might resolve this problem.
Another primary concern is canopy uniformity. Factors affecting uniformity
in emergence, stand, growth, and maturity must be clearly understood in order to
develop viable plant systems for mechanical harvesting (Davis, 1969). Cultural prac-
tices have been discussed that could produce a hedge-row system. However, trees
that require severe hedging to maintain their shape often develop woody structures
near the surface that could be an obstacle to robotically harvesting interior fruit. A
tree that grows to an appropriate mature height and shape and then maintains its size
with either minimal hedging or woody mass buildup would be ideal.
Several plant breeding projects have contributed favorably to mechanical harvest-
ing. Peach (
Prunus persica
) breeders increased fruit harvest by releasing varieties
with varying maturities, effectively doubling or tripling the length of the peach sea-
son in many production areas (Carew, 1969). Dwarfing rootstocks in combination
with apple varieties have provided size control of apple trees. Plant improvement
through breeding can modify crop characteristics and assist in the introduction of
mechanical harvesting systems (Carew, 1969).
7.4.2 D
ESIGN
A
SPECTS
OF
R
OBOTIC
H
ARVESTING
Robotic system developers from the United States, Europe, Israel, and Japan con-
ducted independent research and development on harvesting systems for apples and
citrus during the mid-1980s to 2000, achieving harvesting efficiencies of 75%. These
low levels of performance were attributed to poor fruit identification and the inabil-
ity to negotiate natural obstacles inside the tree canopy (Sarig, 1993). Harvesting
cycle times for citrus were estimated at 2 s/fruit for a two-arm machine (or 4 s/fruit
for a single-arm machine). Cycle times for apples were expected to be higher than
citrus because of improved canopy access (Sarig, 1993). These levels of harvesting
performance and the resulting economic return on investment prevented producer
acceptance.
The focus of most robotic fruit harvesting projects has been to design a harvesting
system that can mimic the precision of a human harvester while improving harvest-
ing efficiency and labor productivity. The typical design of a robotic fruit harvester
consists of a vision system for detecting the fruit, a manipulator that acts like a human
arm, and an end effector to pick the fruit. However, a complete robotic harvesting
system is actually much more complex as can be seen in Figure 7.19, where the sys-
tem architecture illustrates the various functional areas of the robotic system that
begins with the vehicle platform that must provide mobility within the orchard. These
