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Satellite Images-based Obstacle Recognition and Trajectory Generation for Agricultural Vehicles
Author(s) -
Mehmet Bodur,
Moein Mehrolhassani
Publication year - 2015
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/62069
Subject(s) - computer science , trajectory , global positioning system , real time kinematic , obstacle , initialization , computer vision , artificial intelligence , motion planning , field (mathematics) , automation , precision agriculture , real time computing , agriculture , robot , gnss applications , mathematics , telecommunications , physics , astronomy , political science , law , engineering , mechanical engineering , ecology , pure mathematics , biology , programming language
In this study, a method for the generation of tracking trajectory points, detection and positioning of obstacles in agricultural fields have been presented. Our principal contribution is to produce traceable GPS trajectories for agricultural vehicles to be utilized by path planning algorithms, rather than a new path planning algorithm. The proposed system works with minimal initialization requirements, specifically, a single geographical coordinate entry of an agricultural field. The automation of agricultural plantation requires many aspects to be addressed, many of which have been covered in previous studies. Depending on the type of crop, different agricultural vehicles may be used in the field. However, regardless of their application, they all follow a specified trajectory in the field. This study takes advantage of satellite images for the detection and positioning of obstacles, and the generation of GPS trajectories in the agricultural realm. A set of image processing techniques is applied in Matlab for detection and positioning

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