Agriculture Reference
In-Depth Information
was successfully deployed on a fully autonomous stadium mower and a large-scale
peat moss harvesting operation (Zeitzew, 2007).
Multi-Robot Control Architectures—coordinating multiple autonomous robots
for achieving an assigned task presents an engineering challenge. When multiple
robots are working together to accomplish a task, the foremost question to be resolved
is the type of inter-robot communication required. Inter-robot communication forms
the backbone of a multi-robot system (MRS). Identifying the specific advantages of
deploying inter-robot communication is critical as the cost increases with the com-
plexity of communication among the robots. Three types of inter-robot communica-
tion were explored by Balch and Arkin (1994). They found that communication can
significantly improve performance in some cases, but for others, interagent com-
munication is unnecessary. In cases where communication helps, the lowest level of
communication is almost as effective as the more complex type. Rude et al. (1997)
developed a wireless inter-robot communication network called IRoN. The two
important concepts of the network were implicit and explicit communications. A
modest cooperation between robots is realized using implicit communication, and a
dynamic cooperation is achieved by using explicit communication. The authors used
two robots to implement IRoN and were able to identify the changes that reduced the
motion delay time ranges from 50 to 1000 ms. Wilke and Braunl (2001) developed
flexible wireless communication network for mobile robot agents. The communica-
tion network was an explicit communication method that was applied to team mem-
bers of a RoboCup team playing soccer.
To date, most of the research work done on multiagent robot systems has been
conducted in areas other than agriculture. Research work done on the architectural
specifications of an MRS specifically deployed for agricultural production is rarely
found in the literature. Thus, there is a need to understand, explore, and research the
control methodologies of an MRS so that multiple Ag-Robots can be deployed for
agricultural production. Furthermore, the rapidly evolving contemporary agricul-
ture industry may be poised to adopt MRS for increasing production efficiency. The
next-generation machines can be envisioned to accomplish agricultural production
tasks autonomously using the intelligence provided by robust control architectures.
As an example, two autonomous vehicles are assumed to perform baling and bale
moving operations. Establishing communication between the baler and bale spear
vehicles, hay bale location identification, navigation to the bale, spearing of the bale,
and relocation to the edge of the field will be done with minimal human supervi-
sion. Momentary wireless communication is established between the baling and bale
spear vehicles during the spearing operation (see Figure 5.14). The baling vehicle
sends the location where it dropped the hay bale to aid the bale spear vehicle in path
planning. The baling and spearing vehicles each have message frames to communi-
cate the status and location of the bale. When bale is ejected, the vehicle transmits
the location and timestamp through the Tx-message frame to the spear. The infor-
mation about the bale is received by the Rx-message frame of the spearing vehicle
that acknowledges the reception by transmitting a Tx-message frame. The baling
and spearing vehicles, in addition to point-to-point communication, broadcast their
messages with information containing their unique IDs, states, time stamp, and the
status of the assigned work to Central Monitoring Station (CMS).
