Vision Intelligence for Mobile Agro-Robotic System | Zendy

Noboru Noguchi | Zendy; John F. Reid | Zendy; Qin Zhang | Zendy; Lei Tian | Zendy; A. C. Hansen | Zendy

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Vision Intelligence for Mobile Agro-Robotic System

Author(s) -

Noboru Noguchi,

John F. Reid,

Qin Zhang,

Lei Tian,

A. C. Hansen

Publication year - 1999

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.1999.p0193

Subject(s) - fuzzy logic , artificial neural network , artificial intelligence , field (mathematics) , computer science , mobile robot , genetic algorithm , geographic information system , crop , data mining , machine learning , robot , computer vision , geography , mathematics , cartography , pure mathematics , forestry

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 r 2 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.

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