A System to Track the Behaviour or Pattern of Mobile Robot Through RNN Technique

A System to Track the Behaviour or Pattern of Mobile Robot Through RNN Technique

The agricultural business has seen a rise in the use of mobile robots because of their ease of navigation in crop fields. Numerous significant issues pertaining to agricultural robot navigation are covered in this paper, such as obstacle detection, route planning, mapping, localization, and controll...

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Bibliographic Details
Published in:2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) pp. 2003 - 2005
Main Authors: Banu, E.Afreen, Chidambaranathan, Senthilnathan, Jose, Naduvathezhath Nessariose, Kadiri, Padmaja, Abed, Riyad E., Al-Hilali, Aqeel
Format: Conference Proceeding
Language:English
Published: IEEE 14-05-2024
Subjects:
Crops
Humidity
Localization
Location awareness
Mapping
Mobile Robots
Navigation
Recurrent neural networks
RNN
Robot Navigation
sarcasm
Spirals
Velocity control
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Summary:The agricultural business has seen a rise in the use of mobile robots because of their ease of navigation in crop fields. Numerous significant issues pertaining to agricultural robot navigation are covered in this paper, such as obstacle detection, route planning, mapping, localization, and controlled guiding. The proposed hybrid recurrent neural network (RNN) model seeks to optimise mobile autonomous robot tracking performance using installed laser-based weeding equipment. The system can handle a range of trajectories, including curves and straight lines, that are observed in agricultural settings by integrating spiral, lateral, and linear speed controls. A comprehensive field test is carried out on a tracked mobile platform to validate the controllers' functionality in a variety of scenarios, including loose dirt, stones, and humidity.
DOI:10.1109/ICACITE60783.2024.10617430