Agriculture Reference
In-Depth Information
on the information presented in this chapter, the authors believe that we will see
a paradigm shift in the size of field machinery. The first commercially success-
ful autonomous agricultural vehicles will be low power (<30 kW) and lightweight
(<2 T). Principal field tasks will be low-draft operations such as no-till seeding and
spraying. The shift to smaller sized equipment autonomous vehicles will be accom-
panied by a reduction in machine life (<25% of current machines). The philosophy
will be to design vehicles that mechanically fail at about the same point they reach
obsolescence (approximately five cropping seasons). Furthermore, symmetry will
be used to minimize the overall number of parts required to build the power units,
thereby increasing volume and reducing productions costs. Perhaps the most crucial
and tangible benefit to follow from the reduced equipment size will be the ability of
manufacturers and producers to manage the liability of fully autonomous machines.
REFERENCES
Arkin, R.C. 1989. Motor schema-based mobile robot navigation. International Journal of
Robotic Research , 8:92-112.
Arkin, R.C. 1990. Integrating behavioral, perceptual, and world knowledge in reactive naviga-
tion. North Holland Robotics and Autonomous Systems , 6:10-122.
Arkin, R.C. 1998. Behavior-Based Robotics . Cambridge, MA: MIT Press.
ASABE. 2011. D497.6 Agricultural Machinery Management Data. ASABE: St. Joseph, MI.
Auernhammer, H. 1983. Die elektronischeSchnittstelleSchlepper-Gerät. In: Landwirtschaftliches
BUS-System-LBS . Arbeitspapier 196. Darmstadt, Germany: KuratoriumfürTechnik und
Bauwesen in der Landwirtschaft e. V. (KTBL).
Balch, T., and R.C. Arkin. 1994. Communication in reactive multiagent robotic systems.
Autonomous Robots , 1:27-52.
Barreca, S.L. 2000. Technology life-cycles and technological obsolescence. Available at:
http://www.bcri.com/Downloads/Valuation%20Paper.PDF
Blackmore, B.S., H. Have, and S. Fountas. 2001. A specification of behavioural require-
ments for an autonomous tractor (KEYNOTE address). In: M. Zude, B. Herold, and M.
Guyer (Editors), 6th International Symposium on Fruit, Nut and Vegetable Production
Engineering Conference. Potsdam-Bornim, Germany: Institute fürAgrartechnikBorn-
ime, V. pp. 25-36.
Blackmore, B.S., H. Have, and S. Fountas. 2002. A proposed system architecture to enable
behavioural control of an autonomous tractor (keynote address). In: Zhang, Q. (Editor),
Proceedings of Automation Technology for Off-Road Equipment. St. Joseph, MI: ASAE.
pp. 13-23.
Blackmore, B.S., S. Fountas, S. Vougioukas, L. Tang, C.G. Sorensen, and R. Jorgensen. 2004.
A method to define agricultural robot behaviors. In: Proceedings of the Mechatronics
& Robotics Conference (MECHROB). Agrovej, Denmark: The Royal Veterinary and
Agricultural University. pp. 1197-1200.
Benson, E.R., J.F. Reid, and Q. Zhang. 2003. Machine vision-based guidance system for an
agricultural small-grain harvester. Transactions of the ASE, 46:1255-1264.
Brooks, R.A. 1986. A robust layered control-system for a mobile robot. IEEE Journal of
Robotics and Automation , 2:14-23.
Deere and Company. 2010a. iTEC Pro operator's manual. Available at: http://stellarsupport.deere
.com/en_US/support/pdf/om/en/OMPC21754_iTEC.pdf. Accessed October 14, 2010.
Deere and Company. 2010b. 70 Series STS Combine Harvesters: Precision Ag. Available
at: http://www.deere.com/en_AU/equipment/ag/combines/70series/ams.html. Accessed
December 31, 2010.
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