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Multi-Agent Collaborative Framework for Automated Agriculture

Ankit, K and Kolathaya, SNY and Ghose, D (2021) Multi-Agent Collaborative Framework for Automated Agriculture. In: 15th International Conference on Advanced Computing and Applications, 24-26 Nov 2021, Virtual, Online, pp. 30-37.

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Official URL: https://doi.org/10.1109/ACOMP53746.2021.00011


The use of internet-connected devices, especially small multi-rotor Unmanned Aerial Vehicles (UAVs), in scientific data gathering and applications is quite widespread. But due to limited intervention capability, the UAVs alone fail to automate agricultural tasks completely. Thereby, we propose a centralized framework capable of handling a heterogeneous mixture of UAVs and UGVs to cater to the needs of automating agriculture efficiently. The framework's core is a novel heuristic decision module that creates new tasks by visually analyzing the farm and solves a vehicle routing problem to allocate it to agents optimally. It is also equipped with supporting modules to monitor their operation and, in case of failures, help them recover autonomously based on the task and agent assessment. The framework is used in three significant agricultural applications, namely yield prediction and drought stress detection in a simulated environment using ROS and Gazebo, and 3D mapping of a real farm. These applications demonstrate the use of the multi-agent collaborative framework in identifying agricultural tasks on a farm and executing them. © 2021 IEEE.

Item Type: Conference Paper
Publication: Proceedings - 2021 15th International Conference on Advanced Computing and Applications, ACOMP 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords: Agriculture; Antennas; Autonomous agents; Multi agent systems; Vehicle routing; Yield stress, Collaborative framework; Data application; Fault handling; Multi agent; Multi-UAS collaboration; Pick and place; Scientific data; Task planning; Vision based; Vision based pick and place, Unmanned aerial vehicles (UAV)
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited: 09 Mar 2022 10:30
Last Modified: 09 Mar 2022 10:30
URI: http://eprints.iisc.ac.in/id/eprint/71542

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