Development of Cost-Effective and Easily Replicable Robust Weeding Machine—Premiering Precision Agriculture in Pakistan

Author:

Hussain Azmat12ORCID,Fatima Hafiza Sundus12,Zia Syed Mohiuddin12,Hasan Shehzad12,Khurram Muhammad12,Stricker Didier3,Afzal Muhammad Zeshan34

Affiliation:

1. Smart City Lab—National Center of Artificial Intelligence (NCAI), Karachi 75270, Pakistan

2. Computer and Information Systems Department, NED University of Engineering and Technology, Karachi 75270, Pakistan

3. German Research Institute for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany

4. Mindgarage, Technical University of Kaiserslautern, 67663 Kaiserslautern, Germany

Abstract

Weed management has become a highly labor-intensive activity, which is the reason for decreased yields and high costs. Moreover, the lack of skilled labor and weed-resistant herbicides severely impact the agriculture sector and food production, hence increasing the need for automation in agriculture. The use of agricultural robots will help in the assurance of higher yields and proactive control of the crops. This study proposes a laser-based weeding vehicle with a unique mechanical body that is adjustable relative to the field structure, called the Robot Operating System (ROS) based robust control system, and is customizable, cost-effective and easily replicable. Hence, an autonomous-mobile-agricultural robot with a 20 watt laser has been developed for the precise removal of weed plants. The assembled robot’s testing was conducted in the agro living lab. The field trials have demonstrated that the robot takes approximately 23.7 h at the linear velocity of 0.07 m/s for the weeding of one acre plot. It includes 5 s of laser to kill one weed plant. Comparatively, the primitive weeding technique is highly labor intensive and takes several days to complete an acre plot area. The data presented herein reflects that implementing this technology could become an excellent approach to removing unwanted plants from agricultural fields. This solution is relatively cost-efficient and provides an alternative to expensive human labor initiatives to deal with the increased labor wages.

Funder

DAAD

German-Pakistani Research Cooperation program

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Optimization,Mechanical Engineering,Computer Science (miscellaneous),Control and Systems Engineering

Reference34 articles.

1. Healy, J., Nicholson, D., and Gahan, P. (2017). Book: The Future of Work in Australia: Anticipating How New Technologies Will Reshape Labour Markets, Occupations and Skill Requirements.

2. An autonomous strawberry-harvesting robot: Design, development, integration, and field evaluation;Xiong;J. Field Robot.,2020

3. A review on application of technology systems, standards and interfaces for agriculture and food sector;Suprem;Comput. Stand. Interfaces,2013

4. Soil compaction and soil management—A review;Batey;Soil Use Manag.,2009

5. Pedersen, S.M., Fountas, S., and Blackmore, S. (2008). Service Robot Applications, IntechOpen.

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Development of a prototype of weeding robot;Engineering Research Express;2024-03-01

2. Deep Learning-Based Weed–Crop Recognition for Smart Agricultural Equipment: A Review;Agronomy;2024-02-11

3. Based on Hybrid Densenet-121 with Support Vector Machine Algorithm for Lettuce and Chili;2023 IEEE International Conference on Mechatronics and Automation (ICMA);2023-08-06

4. Design of Smart Weed Detection and Evacuation Robot Using TensorFlow Model Maker;Proceedings of Data Analytics and Management;2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3