JRM Vol.11 No.3 pp. 193-199
doi: 10.20965/jrm.1999.p0193


Vision Intelligence for Mobile Agro-Robotic System

Noboru Noguchi*, John F. Reid**, Qin Zhang**, Lei Tian** and Al C. Hansen***

*Bioproduction Enginering, School of Agriculture, Graduate School of Hokkaido University, Sapporo, Japan

**Department of Agricultural Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, U.S.A.

***Department of Agricultural Engineering, University of Natal, Scottsville, South Africa

February 1, 1999
March 8, 1999
June 20, 1999
fuzzy logic, genetic algorithms, neural networks, machine vision, artificial intelligence, precision farming, geographic information system, global positioning system
We developed an intelligent vision system for mobile robot field operations. Fuzzy logic was used to classify crops and weeds. A genetic algorithm (GA) was used to optimize and tune fuzzy logic membership rules. Field studies confirmed that our method accurately classified crops and weeds throughout their growth cycle. After separating out weeds, an artificial neural network (ANN) was used to estimate crop height and width. The r2 for estimating crop height was 0.92 for training data and 0.83 for test data. A geographic information system (GIS) was used to create a crop growth map.
Cite this article as:
N. Noguchi, J. Reid, Q. Zhang, L. Tian, and A. Hansen, “Vision Intelligence for Mobile Agro-Robotic System,” J. Robot. Mechatron., Vol.11 No.3, pp. 193-199, 1999.
Data files:

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jun. 19, 2024