Cruz Ulloa, Christyan; Barrientos, Antonio; Cerro, Jaime; Krus, Anne and Valero, Constantino (2020) Robot localization in changing organic strip-cropping environments through point clouds. Working paper. [Completed]
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Summary
This presentation is aimed at estimating the position of the robot in row crops despite continuous changes in the environment (due to wind or small plant growth), using a LiDAR sensor to obtain global point clouds (previously registered, all-terrain) and local point clouds (from one part of the ground obtained during the advance of the robot), in fertilization tasks
EPrint Type: | Working paper |
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Teaser: | Results show that using the adequate extraction of characteristics in global and local point cloud maps, it is possible to determine the robot's relative position for fertilization tasks (blue) and the sensor (red) concerning the crop. This technique has applications in a variety of crops due to wind or small plant growth. |
What problem does the tool address?: | Using robotics for targeted fertilisation in a strip-crop environment |
What solution does the tool offer?: | How to train a robot to find individual plants for individualized fertilization |
Country: | Spain |
Keywords: | robot, fertilization, organic, LiDAR, point cloud, local positioning |
Agrovoc keywords: | Language Value URI English strip cropping http://aims.fao.org/aos/agrovoc/c_25705 English robots http://aims.fao.org/aos/agrovoc/c_25680 |
Subjects: | Crop husbandry > Crop combinations and interactions Farming Systems > Buildings and machinery |
Research affiliation: | European Union > CORE Organic > CORE Organic Cofund > SUREVEG Spain > CSIC (Spanish National Research Council) Spain > Polytechnic University of Madrid |
Horizon Europe or H2020 Grant Agreement Number: | 727495 |
Deposited By: | Valero, Constantino |
ID Code: | 43289 |
Deposited On: | 01 Feb 2022 07:29 |
Last Modified: | 01 Feb 2022 07:29 |
Document Language: | English |
Status: | Unpublished |
Refereed: | Not peer-reviewed |
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