Author:
Mowshowitz Abbe,Tominaga Ayumu,Hayashi Eiji, ,
Abstract
This paper addresses the problem of using a mobile, autonomous robot to manage a forest whose trees are destined for eventual harvesting. “Manage” in this context means periodical weeding between all the trees in the forest. We have constructed a robotic system enabling an autonomous robot to move between the trees without damaging them and to cut the weeds as it traverses the forest. This was accomplished by 1) computing a trajectory for the robot in advance of its entrance into the forest, and 2) developing a program and equipping the robot with the instruments needed to follow the trajectory. Computation of a trajectory in a forest is facilitated by treating the trees as vertices in a graph. Current, laser-based instruments make it possible to identify individual trees and compute distances between them. With this information a forest can be represented as a weighted graph. This graph can then be modified systematically in a way that allows for computing a Hamiltonian circuit that passes between each pair of trees. This representation is an instance of the well known Travelling Salesman Problem. The theory was put into practice in an experimental forest located at the Kyushu Institute of Technology. Our robot “SOMA,” built on an ATV platform, was able to follow a part of the trajectory computed for this small forest, thus demonstrating the feasibility of forest maintenance by an autonomous, labor saving robot.
Publisher
Fuji Technology Press Ltd.
Subject
Electrical and Electronic Engineering,General Computer Science
Reference13 articles.
1. R. Parker, K. Bayne, and P. W. Clinton, “Robotics in Forestry,” New Zealand J. of Forestry, Vol.60, pp. 8-14, 2016.
2. G. Brolly and G. Király, “Algorithms for Stem Mapping by Means of Terrestrial Laser Scanning,” Acta Silv. Lign. Hung., Vol.5, pp. 119-130, 2009.
3. M. Holopainen, M. Vastaranta, and J. Hyyppä, “Outlook for the Next Generation’s Precision Forestry in Finland,” Forests, Vol.5, pp. 1682-1694, 2014.
4. H.-G. Maas, A. Bienert, S. Scheller, and E. Keane, “Automatic Forest Inventory Parameter Determination from Terrestrial Laser Scanner Data,” Int. J. of Remote Sensing, Vol.29, No.5, pp. 1579-1593, 2008.
5. T. Ritter, M. Schwarz, A. Tockner, F. Leisch, and A. Nothdurft, “Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning,” Forests, Vol.8, No.8, pp. 1-19, 2017.
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献