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Vision Intelligence for Mobile Agro-Robotic System

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

Abstract:
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.

Keywords: fuzzy logic, genetic algorithms, neural networks, machine vision, artificial intelligence, precision farming, geographic information system, global positioning system

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