Canadian Forest Service Publications

Autonomous forest stand-tending robots. 1993. Kourtz, P.H.; Strome, M.; Gougeon, F.A. Pages 70-78 in M. Köhl and G.Z. Gertner, editors. Proceedings of the IUFRO Meeting on Statistics, Methods, Mathematics and Computers, August 30-September 4, 1992, Berlin/Eberswalde, Germany. WSL/FNP, Birmensdorf, Switzerland, IUFRO S4.11-00.

Year: 1993

Issued by: National Capital Region

Catalog ID: 10797

Language: English

Availability: Order paper copy (free), PDF (request by e-mail)

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Abstract

Forestry is a major contributor to Canada's gross national product and Canada is committed to the concept of sustainable development for its forest resources to ensure that the economic, social, and ecological benefits accruing from our vast forest land will be enjoyed by Canadians in perpetuity. To achieve this goal, it will be necessary to increase the intensity of silvicultural operations in our forests. However, it is unlikely that we will have the necessary human resources to carry out these operations, or that intensive manual operations will be economically practical. Small autonomous robots, functioning much like persons with brush saws, offer the potential to carry out stand-tending operations in a cost-effective manner.
The Petawawa National Forestry Institute (PNFI) has recently begun a project aimed at the eventual development of such a robot for weeding, brushing, and thinning in young conifer stands. It is a very long term, low budget project that takes advantage of in-house resources and those of our cooperators. The development work, supported by corresponding research, will proceed in an evolutionary manner, beginning with simple forest environments and primitive machines. Subsumption robotic architecture will be employed. Machines will be developed to demonstrate concepts and, hopefully, these will eventually evolve into useful prototypes. Petawawa is not in the machine manufacturing business; we expect that the Canadian robotics industry will produce the first operational machines based on the results of our work.
Forest vision is anticipated to be the major research problem. The machine must be able to recognize future crop trees and remove other competing vegetation. The Institute is well equipped to carry out the necessary machine development and vision research, having a world-class digital remote sensing laboratory, plenty of expertise in artificial intelligence, and an experimental forest on site.