Agriculture Reference
In-Depth Information
reasons for this lack of success are attributable to technical, economic, horticultural,
and producer acceptance issues. In industrial automation applications, the robots'
environment is designed for optimal performance, eliminating as many variables as
possible through careful systems planning. In agricultural settings, environmental
and horticultural control can be a significant hurdle to successful automation. Not
only must the plant system be designed for successful automation, but the cultural
and horticultural practices used by the producers must often be changed to provide
a plant growth environment in which robotic systems can be successful. According
to Sarig (1993), “The major problems that must be solved with a robotic picking
system include recognizing and locating the fruit, and detaching it according to pre-
scribed criteria, without damaging either the fruit or the tree. In addition, the robotic
system needs to be economically sound to warrant its use as an alternative method
to hand picking.” A successful robotic harvesting system must be able to satisfy
the following constraints: (1) picking rate of fruits should be faster than or equal to
manual picking, (2) fruit quality should be equal to or better than manual picking,
and (3) should be economically justifiable.
Economic analysis of robotic citrus harvesting was carried out by Harrell et al.
(1988), who identified 19 factors that affect harvesting costs and concluded that
robotic citrus harvesting cost was still greater than hand harvesting cost. They found
that robotic harvest cost was primarily affected by harvest inefficiency, followed by
harvester purchase price, average picking cycle time, and harvester repair expense.
They concluded that robotic harvesting technology research and development should
continue and concentrate on the following areas: (1) harvest inefficiency, (2) pur-
chase price, (3) harvester reliability, and (4) modifications in work environment that
would improve performance of robotic harvesters. Furthermore, it was found that the
robotic harvest cost was most sensitive to harvest inefficiency. Therefore, it was rec-
ommended that the primary design objective would be to minimize harvesting inef-
ficiency. They concluded that a harvesting efficiency of 93-99% would be required
before robotic harvesting reaches breakeven point with manual labor at current har-
vesting costs.
Robots tend to perform well in a structured environment, where the position and
orientation of the target is known or targets can be set up in the desired position and
orientation. However, harvesting fruit and vegetable crops robotically in unstructured
environments create a new set of challenges because many of the aspects relied on
by industrial robots do not exist. Challenging design conditions include nonuniform
lighting ranging from direct sunlight to overcast and twilight conditions, variable
temperature and humidity, wet and dry conditions, variable fruit sizes and maturity,
nonuniform plant size and fruit position, fruit occlusions and limb obstacles, mobile
power supplies, and a dirty harsh environment. Add to these the requirement for low-
cost equipment solutions and you have a very difficult engineering design require-
ment, which explains the low development success rate.
The objective of this section is to present an overview of the major horticultural
and engineering aspects of robotic harvesting systems for tree crops. To provide the
reader with sufficient breadth of information, this section is primarily a survey that
tries to identify the key issues that robotic system developers and horticultural scien-
tists should consider to optimize plant-machine system performance.
