Authors:
Joaquín Torres-Sospedra
and
Patricio Nebot
Affiliation:
Universitat Jaume I, Spain
Keyword(s):
Outdoor mobile robotics, Agricultural environments, Visual path planner, Ensembles of neural networks.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Mobile Robots and Autonomous Systems
;
Robotics and Automation
;
Vehicle Control Applications
;
Vision, Recognition and Reconstruction
Abstract:
One of the most important system to deploy for a robot navigating in an outdoor scenario, as can be an orange grove, is the navigation system. In this paper, a path planner in orange groves for an autonomous robotic system is presented. This path planner is based on a previous classification of the image that the robot gets from its visual sensory system. One of the most important technique used to generate accurate classifiers is based on training an ensemble of neural networks. Here, a simple ensemble of neural networks is used to classify images from an orange grove using wavelets features. With the classification image obtained, the most important lines of the land are extracted with the Hough transform. The final path line is determined with these lines. The purpose of this paper is to determine if the ensemble approach can be useful in the procedure to design an accurate path planner for outdoor autonomous robots in orange groves. The published results show that ensembles can b
e considered for this type of applications.
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