Cooperation of unmanned systems for agricultural applications: A theoretical framework

Mammarella, Martina; Comba, Lorenzo; Biglia, Alessandro; Dabbene, Fabrizio; Gay, Paolo

doi:10.1016/j.biosystemseng.2021.11.008

Cited by 29 publications

(9 citation statements)

References 94 publications

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“…Quadcopters are very versatile unmanned aerial vehicles (UAV) due to their diverse capabilities for civilian and military applications [1]. Cooperative payload transport is one of the applications that has recently attracted the attention of researchers [2] because it can be used for transporting medical packages to rural areas that are difficult to access [3], transporting tanks with chemicals for crop spraying [4], transporting loads for construction processes [5], etc.…”

Section: A Context and Motivationsmentioning

confidence: 99%

A Novel Neural Network-Based Robust Adaptive Formation Control for Cooperative Transport of a Payload Using Two Underactuated Quadcopters

Ccari

Yanyachi

2023

IEEE Access

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supports the financial processing charges (APC) of the IEEE journal for the publication ABSTRACT Designing a controller for the cooperative transport of a payload using quadcopter-type unmanned aerial vehicles (UAVs) is a very challenging task in control theory because these vehicles are underactuated mechanical systems. This paper presents a novel robust adaptive formation control design for the cooperative transport of a suspended payload by ropes using two underactuated quadcopters in the presence of external disturbances and parametric uncertainties. The structure of the proposed controller is divided into two subsystems: fully actuated and underactuated. An integral sliding mode adaptive control strategy is proposed for the fully actuated subsystem, and for the underactuated subsystem, an adaptive control strategy based on the combination of Backstepping and sliding mode is proposed. Then, the control parameters of the sliding surfaces of both control subsystems are adaptively tuned by a neural network. In addition, to improve the robustness of the proposed controller, a disturbance observer is incorporated to estimate and compensate the lumped disturbances. The asymptotic stability of the cooperative transport system is verified with the Lyapunov theorem. Finally, numerical simulations are performed in MATLAB/Simulink environment, and the results show that the proposed controller successfully transports the payload safely and without oscillations. Moreover, the desired formation pattern is maintained throughout the flight task, even with external disturbances and parametric uncertainties.

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Section: A Context and Motivationsmentioning

confidence: 99%

A Novel Neural Network-Based Robust Adaptive Formation Control for Cooperative Transport of a Payload Using Two Underactuated Quadcopters

Ccari

Yanyachi

2023

IEEE Access

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“…As manual labour in the field had mainly been substituted with agricultural machines, now operators of these machines are being substituted with computers [134,135]. Modern agricultural robots can provide more than just traditional machinery substitution (land preparation, sowing, planting, plant treatment, harvesting) [136], such new functions are mapping, insect pest monitoring, artificial pollination, yield estimation and phenotyping [137].…”

Section: Electric and Unmanned Agricultural Vehicles Robotisationmentioning

confidence: 99%

A Mini-Review of Current Activities and Future Trends in Agrivoltaics

Klokov¹,

Loktionov²,

Loktionov³

et al. 2023

Preprint

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Agrivoltaics (Agri-PV, AV) – the joint use of land for the production of agricultural products and energy – has recently been rapidly gaining popularity, as it can significantly increase income per unit of land area. In a broad sense, AV systems can include converters of not only solar, but also energy from any other local renewable source, including bioenergy. Current approach to AV represents an evolutionary development of agroecology and integrated PV power supply to the grid. That results in nearly doubled income per unit area. While AV could provide a basis for revolution in large-scale unmanned precision agriculture and smart farming which is impossible without on-site power supply, chemical fertilisation and pesticides reduction, and yield processing on-site. These approaches could change the logistics and the added value production chain in agriculture dramatically, and so, reduce its carbon footprint. Utilisation of decommissioned solar panels in AV could make the technology twice cheaper and postpone the need for bulk PV recycling. Unlike the mainstream discourse on the topic, this review feature is in focusing on the possibilities for AV to be stronger integrated into agriculture that could also help in relevant legal collisions (considered as neither rather than both components) resolution.

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“…A theoretical framework for cooperation between multiple UAV systems appears in [49], where a large agricultural land is divided into multiple regions with one UAV (MULT-UAV) dedicated to each of those regions. However, the method is very expensive because of the requirement to deploy such an average number of aerial vehicles.…”

Section: Related Workmentioning

confidence: 99%

Support Vector Machine-Based Energy Efficient Management of UAV Locations for Aerial Monitoring of Crops over Large Agriculture Lands

Al-Naeem

Rahman

Banerjee³

et al. 2023

Sustainability

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Crop monitoring and smart spraying have become indispensable parts of precision agriculture where unmanned aerial vehicles (UAVs) play a lead role. In particular, in large agricultural fields, aerial monitoring is a sustainable solution provided it can be performed in an energy-efficient manner. The existing literature points out that the research on precision agriculture using UAVs is still very minimal. In this article, we propose a support vector machine (SVM)-based UAV location management technique where UAVs change position over various portions or regions of a large agricultural field so that crops are properly monitored in an energy-efficient manner. Whenever a processing request is generated from any sensor in a part of the field, the UAV investigates with an SVM to decide whether to move on to the center of that field based on various parameters or characteristics such as region-id, packet-id, time of day, waiting times of the packets, the average waiting time of others within a predefined time window, location of the UAV, residual energy of the UAV after processing the packet, and movement after processing the packet. We use 70% of our data for training and the other 30% for testing. In our simulation study, we use accuracy, precision, and recall to measure in both contexts to determine the efficiency of the model, and also the amount of energy preserved is computed corresponding to every move. We also compare our approach with current state-of-the-art energy-preserving UAV movement control techniques which are compatible with the present application scenario. The proposed technique produced 6.5%, 34.5%, and 61.5% better results in terms of percentage of successful detection (PSD), composite energy consumption (CEC), and average delay (ADL), respectively.

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Cooperation of unmanned systems for agricultural applications: A theoretical framework

Cited by 29 publications

References 94 publications

A Novel Neural Network-Based Robust Adaptive Formation Control for Cooperative Transport of a Payload Using Two Underactuated Quadcopters

A Novel Neural Network-Based Robust Adaptive Formation Control for Cooperative Transport of a Payload Using Two Underactuated Quadcopters

A Mini-Review of Current Activities and Future Trends in Agrivoltaics

Support Vector Machine-Based Energy Efficient Management of UAV Locations for Aerial Monitoring of Crops over Large Agriculture Lands

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