Guevara, Leonardo, Michałek, Maciej Marcin and Auat Cheein, Fernando (2020) Headland turning algorithmization for autonomous N-trailer vehicles in agricultural scenarios. Computers and Electronics in Agriculture, 175 . p. 105541. ISSN 0168-1699
Full content URL: https://doi.org/10.1016/j.compag.2020.105541
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Headland turning algorithmization - submitted.pdf - Whole Document Restricted to Repository staff only 6MB |
Item Type: | Article |
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Item Status: | Live Archive |
Abstract
Articulated vehicles composed of a tractor and several passive trailers are commonly used for transportation purposes in agricultural applications. The increment of the number of trailers increases the payload capacity, but on the other hand, it also implies serious motion constraints, especially in turning scenarios where there is a greater risk of collisions with the crops. In this context, to reduce dangerous maneuvers during the headland turning scenarios, this paper presents a headland turning algorithmization for the N-trailers, characterized by unifying the motion planning stage with the motion control stage, in contrast to most of the available solutions which treat these stages independently. The proposed algorithmization delivers an admissible headland reference path and the location of the vehicle guidance point for the path-following task, to reduce both possible collisions with the crop and the inter-segment collisions. The proposed approach was validated by solving several illustrative problems which address various field/crop dimensions and vehicles with different number of trailers. The results showed that the proposed system can find and execute a safe maneuver in a broad range of known situations from the agricultural domain.
Keywords: | N-trailers, Motion Control, motion and path planning, Articulated vehicles, agricultural machinery, Collision avoidance |
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Subjects: | H Engineering > H660 Control Systems H Engineering > H131 Automated Engineering Design H Engineering > H671 Robotics H Engineering > H130 Computer-Aided Engineering |
Divisions: | College of Science > Lincoln Institute for Agri-Food Technology |
ID Code: | 53536 |
Deposited On: | 06 Mar 2023 15:55 |
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