Heterogeneous Multi-Robot System for Mapping Environmental Variables of Greenhouses

Roldán, Juan Jesús; Garcia-Aunon, Pablo; Garzón, Mario; León, J. de la Fuente; Cerro, Jaime del; Barrientos, Antonio

doi:10.3390/s16071018

Cited by 96 publications

(52 citation statements)

References 58 publications

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“…Since 2009, the number of papers describing UAV application to plant sciences has also grown exponentially, probably related to the general release of commercial civilian UAVs, such as DJI® or Mikrokopter®, both released in 2006. Intriguingly, only two papers have focused on direct application of very small drones to agriculture (Roldán, Joossen, Sanz, del Cerro, & Barrientos, 2015; Roldán et al., 2016).…”

Section: Big Problems Small Solutionsmentioning

confidence: 99%

Nano and Micro Unmanned Aerial Vehicles (UAVs): A New Grand Challenge for Precision Agriculture?

et al. 2020

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By collecting data at spatial and temporal scales that are inaccessible to satellite and field observation, unmanned aerial vehicles (UAVs) are revolutionizing a number of scientific and management disciplines. UAVs may be particularly valuable for precision agricultural applications, offering strong potential to improve the efficiency of water, nutrient, and disease management. However, some authors have suggested that the UAV industry has overhyped the potential value of this technology for agriculture, given that it is difficult for non‐specialists to operate UAVs as well as to process and interpret the resulting data. Here, we analyze the barriers to applying UAVs for precision agriculture, which range from regulatory issues to technical requirements. We then evaluate how new developments in the nano‐ and micro‐UAV (NAV and MAV, respectively) markets may help to overcome these barriers. Among the possible breakthroughs that we identify is the ability of NAV/MAV platforms to directly quantify plant traits using methods (e.g., object‐oriented classification) that require less image calibration and interpretation than spectral index–based approaches. We suggest that this potential, when combined with steady improvements in sensor miniaturization, flight precision, and autonomy as well as cloud‐based image processing, will make UAVs a tool with much broader adoption by agricultural managers in the near future. If this wider uptake is realized, then UAVs have real potential to improve agriculture's resource‐use efficiency. © 2020 by John Wiley & Sons, Inc.

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Section: Big Problems Small Solutionsmentioning

confidence: 99%

Nano and Micro Unmanned Aerial Vehicles (UAVs): A New Grand Challenge for Precision Agriculture?

et al. 2020

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“…These robots have great advantageous for digital farming. For example, a heterogeneous Multi-Robot system compromising a ground mobile platform and an aerial vehicle ( Figure 7) for mapping environmental variables of greenhouses has been simulated in the Unity3D 5.2.1 game engine [205] . This robot can measure the temperature, humidity, luminosity and carbon dioxide concentration in the ground and at different heights.…”

Section: Agricultural Robotics and Digital Farmingmentioning

confidence: 99%

“…a. Air-ground Multi-Robot platform and its simulation in Unity3D [205] b. Project MARS [146,147] c. A Swarm of Nano Quadrotors Source: TheDmel Youtube channel Figure 7 Examples of Multi-Robot systems for digital farming…”

Section: Agricultural Robotics and Digital Farmingmentioning

confidence: 99%

Research and development in agricultural robotics: A perspective of digital farming

Shamshiri¹,

Weltzien²,

Hameed³

et al. 2018

International Journal of Agricultural and Biological Engineering

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Digital farming is the practice of modern technologies such as sensors, robotics, and data analysis for shifting from tedious operations to continuously automated processes. This paper reviews some of the latest achievements in agricultural robotics, specifically those that are used for autonomous weed control, field scouting, and harvesting. Object identification, task planning algorithms, digitalization and optimization of sensors are highlighted as some of the facing challenges in the context of digital farming. The concepts of multi-robots, human-robot collaboration, and environment reconstruction from aerial images and ground-based sensors for the creation of virtual farms were highlighted as some of the gateways of digital farming. It was shown that one of the trends and research focuses in agricultural field robotics is towards building a swarm of small scale robots and drones that collaborate together to optimize farming inputs and reveal denied or concealed information. For the case of robotic harvesting, an autonomous framework with several simple axis manipulators can be faster and more efficient than the currently adapted professional expensive manipulators. While robots are becoming the inseparable parts of the modern farms, our conclusion is that it is not realistic to expect an entirely automated farming system in the future.

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“…agriculture. The work in [7] has proposed the use of a team of UASs and UGVs for environmental monitoring in greenhouses especially in the presence of obstacles in the greenhouse.…”

Section: School Of Electrical and Computer Engineering University Of Gementioning

confidence: 99%

Coverage Control with Multiple Ground Robots for Precision Agriculture

Davoodi¹,

Velni²,

Li³

2018

Mechanical Engineering

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In this work, coverage of agricultural ﬁelds using a team of autonomous unmanned ground robots with no human intervention is investigated. To this end, ﬁeld is ﬁrst represented by a topological mapandthenadistributedenergy-awaredeployment strategy is proposed to optimally distribute robots with the aim of persistent monitoring of speciﬁed regions of interest. When a robot participating in the coverage task approaches a low energy reserve, the team of robots collectively and cooperatively adjust the coverage formation to allow the agent to return to a designated base station, where it can recharge before rejoining the effort. Preliminary (simulation) results are provided to show the effectiveness and capabilities of the proposed coverage algorithm.

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Heterogeneous Multi-Robot System for Mapping Environmental Variables of Greenhouses

Cited by 96 publications

References 58 publications

Nano and Micro Unmanned Aerial Vehicles (UAVs): A New Grand Challenge for Precision Agriculture?

Nano and Micro Unmanned Aerial Vehicles (UAVs): A New Grand Challenge for Precision Agriculture?

Research and development in agricultural robotics: A perspective of digital farming

Coverage Control with Multiple Ground Robots for Precision Agriculture

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