GPS Based Autonomous Agricultural Robot

Shaik, Kareemulla; Prajwal, Edwin; Sujeshkumar, B; Bonu, Mahesh; Balapanuri, Vamseedhar Reddy

doi:10.1109/icdi3c.2018.00030

Cited by 26 publications

(4 citation statements)

References 4 publications

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“…Most of them are lightweight, with two to four active wheels, and they have cameras, GPS, gyroscopes, magnetometers, and moisture sensors for sensing; additionally, some of them are equipped with tools for manipulation, such as actuators and cutting tools. Detailed information on their characteristics can be found in [50][51][52][53][54]. The lightweight and possible autonomous design is a modern trend for deploying small, human potential-oriented agricultural robots that are able to work in swarms for accomplishing agricultural tasks and are quite affordable by the comparatively poor farmers and are in line with the directions for sustainable and environmentally friendly development [21][22][23]55].…”

Section: Discussionmentioning

confidence: 99%

Enhanced Robots as Tools for Assisting Agricultural Engineering Students’ Development

et al. 2022

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Inevitably, the rapid growth of the electronics industry and the wide availability of tailored programming tools and support are accelerating the digital transformation of the agricultural sector. The latter transformation seems to foster the hopes for tackling the depletion and degradation of natural resources and increasing productivity in order to cover the needs of Earth’s continuously growing population. Consequently, people getting involved with modern agriculture, from farmers to students, should become familiar with and be able to use and improve the innovative systems making the scene. At this point, the contribution of the STEM educational practices in demystifying new areas, especially in primary and secondary education, is remarkable and thus welcome, but things become quite uncertain when trying to discover efficient practices for higher education, and students of agricultural engineering are not an exception. Indeed, university students are not all newcomers to STEM and ask for real-world experiences that better prepare them for their professional careers. Trying to bridge the gap, this work highlights good practices during the various implementation stages of electric robotic ground vehicles that can serve realistic agricultural tasks. Several innovative parts, such as credit card-sized systems, AI-capable modules, smartphones, GPS, solar panels, and network transceivers are properly combined with electromechanical components and recycled materials to deliver technically and educationally meaningful results.

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Section: Discussionmentioning

confidence: 99%

Enhanced Robots as Tools for Assisting Agricultural Engineering Students’ Development

et al. 2022

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“…This framework is very much convenient for rancher to operate, as they could effectively perform ploughing, sowing, pruning, harvesting and watering using simple smart phone application. This framework implementation will lead forward value decline, stock saving, and beneficial management in horticulture [8].…”

Section: Objectivesmentioning

confidence: 99%

Solar based multi functional Agricultural Robot using Arduino

Faheema¹

2022

IJEREEE

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Horticulture robotics has thrown a consistent boost with the innovative automation into an entire substructure, for example, farming, pursuing crops, rover service, cultivating, workshop. By considering the importance of robots, yielding of professional’s are being done in order to elaborate the robot applications. Flying robot, lettuce bot, robot milker, versatile robots are some of the sincere dedication done by the researchers towards the agriculture and even for mankind. Horticulture robot consists of an instrument called as an end effector at the end finish of a mechanical arm which is used for various farming and agriculturing activities. Robots are used as an alternative to the human activities in the various field including agriculture such as driverless tractor, sprayer, seed sowers, sheep shearing etc. The alternative utilization of robots can be done in the symbolization of greenery for example showering, checking, weeding, pruning etc. Here the main purpose of our tender Setup is to assist rancher in furrowing, reaping, soil dampness checking etc. This assessment expected to investigate an establishment using a keen framework which utilizes an inserted framework with solar panel and smart phone for horticulture and basic reasoning using an Arduino mega. The disclosures of this examination found that the structure could screen enveloping soil conditions relying upon that watering will be finished. The casing work was seen to be pleasant for ranchers to use and they can feasibly control the bot realizing cost decline, asset saving and productive organization in horticulture.

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“…Agriculture information system (AIS) employs modern technologies like information and communication technology [3], wireless sensors [4], internet of things [5], satellite data [6], and drone images [7] become vital to keep agriculture sustainable, viable, smart and adaptive to future challenges. A traditional agriculture information system uses global positioning system (GPS) for accurate mapping of agricultural fields [8]. Another cost optimized solution -Differential Global Positioning System (DGPS) uses localized data for robot guidance [9].…”

Section: Introductionmentioning

confidence: 99%

Development of an Adaptive Linear Mixture Model for Decomposition of Mixed Pixels to Improve Crop Area Estimation Using Artificial Neural Network

Dwivedi

Singh

et al. 2023

IEEE Access

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Precise spatial information of crop distribution is vital for government and research organizations to monitor agriculture activities like crop health monitoring, crop yield prediction, and food security. Mapping of crop area is challenging in smallholder farming like India, where crop parcels are smaller than two hectares. With an extension of artificial intelligence, an artificial neural network has ability to learn the spectral feature of multispectral satellite images and map them to a land cover class. However, mixed pixel is a challenging problem in pixel wise classification of coarse resolution satellite images. The linear mixture model is successfully utilized to unmix the signals of a mixed classes. The success of linear mixture model is depending on the selection of endmembers of a mixed class. Therefore, this paper presents an adaptive approach for automatic selection of endmembers of a mixed pixel in linear mixture model using spectral and spatial information. The proposed approach is capable of extracting the fraction area cover of each class by using a constrained least-squares error solution. The GPS field surveys, and drone images are employed to create reference data for the accuracy assessment of proposed algorithm. The experimentation results indicate that the solution of the proposed approach outperformed recent baseline methods in terms of efficiency and accuracy of pixelwise estimated area and overall estimated area of various land cover classes.INDEX TERMS Smallholder farming, area estimation, artificial neural network, linear mixture model, mixed pixels, precision agriculture monitoring.

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GPS Based Autonomous Agricultural Robot

Cited by 26 publications

References 4 publications

Enhanced Robots as Tools for Assisting Agricultural Engineering Students’ Development

Enhanced Robots as Tools for Assisting Agricultural Engineering Students’ Development

Solar based multi functional Agricultural Robot using Arduino

Development of an Adaptive Linear Mixture Model for Decomposition of Mixed Pixels to Improve Crop Area Estimation Using Artificial Neural Network

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