A Control  Method for a Swarm of Plant Pot Robots that Uses Artificial Potential Fields for Effective Utilization of Sunlight

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00260004/13.jpg"" width=""300"" />Plant pot robots “Plantroid”</span></div> Plant production factories and agricultural robots are being studied and developed these days. In these cultivation systems, however, it has been difficult to manage the state of each individual plant. We propose a cultivation system that uses a swarm of plant pot robots to automatically move each plant to an optimal environment, based on the plant’s sensory information and surroundings. In this paper, we propose a control method for the swarm of plant pot robots that uses artificial potential fields for effective temporal and spatial utilization of sunlight, and we show its effectiveness through simulation and experimentation. </span>

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1A1-H01 Control Method of Plant Pot Robots using Artificial Potential Fields for Efective Utilization of Sunlight(Robotics and Mechatronics in Agriculture)

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ◽

10.1299/jsmermd.2012._1a1-h01_1 ◽

2012 ◽

Vol 2012 (0) ◽

pp. _1A1-H01_1-_1A1-H01_4

Author(s):

Masato Yuasa ◽

Ikuo Mizuuchi

Keyword(s):

Control Method ◽

Potential Fields ◽

Artificial Potential Fields

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Formation control method based on artificial potential fields for aircraft flight simulation

SIMULATION ◽

10.1177/00375497211063380 ◽

2021 ◽

pp. 003754972110633

Author(s):

Andre N Costa ◽

Felipe LL Medeiros ◽

Joao PA Dantas ◽

Diego Geraldo ◽

Nei Y Soma

Keyword(s):

Formation Control ◽

Control Method ◽

Flight Simulation ◽

Potential Fields ◽

Large Set ◽

Control Approach ◽

Artificial Potential Fields ◽

Optimization Methodology ◽

Cognition Model ◽

Best Parameter

As simulation becomes more present in the military context for variate purposes, the need for accurate behaviors is of paramount importance. In the air domain, a noteworthy behavior relates to how a group of aircraft moves in a coordinated way. This can be defined as formation flying, which, combined with a move-to-goal behavior, is the focus of this work. The objective of the formation control problem considered is to ensure that simulated aircraft fly autonomously, seeking a formation, while moving toward a goal waypoint. For that, we propose the use of artificial potential fields, which reduce the complexities that implementing a complete cognition model could pose. These fields define forces that control the movement of the entities into formation and to the prescribed waypoint. Our formation control approach is parameterizable, allowing modifications that translate how the aircraft prioritize its sub-behaviors. Instead of defining this prioritization on an empirical basis, we elaborate metrics to evaluate the chosen parameters. From these metrics, we use an optimization methodology to find the best parameter values for a set of scenarios. Thus, our main contribution is bringing together artificial potential fields and simulation optimization to achieve more robust results for simulated military aircraft to fly in formation. We use a large set of scenarios for the optimization process, which evaluates its objective function through the simulations. The results show that the use of the proposed approach may generate gains of up to 27% if compared to arbitrarily selected parameters, with respect to one of the metrics adopted. In addition, we were able to observe that, for the scenarios considered, the presence of a formation leader was an obstacle to achieving the best results, demonstrating that our approach may lead to conclusions with direct operational impacts.

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Adaptive Artificial Potential Fields with Orientation Control Applied to Robotic Manipulators

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2020.12.2706 ◽

2020 ◽

Vol 53 (2) ◽

pp. 9924-9929

Author(s):

Caio Cristiano Barros Viturino ◽

Ubiratan de Melo Pinto Junior ◽

André Gustavo Scolari Conceição ◽

Leizer Schnitman

Keyword(s):

Robotic Manipulators ◽

Potential Fields ◽

Orientation Control ◽

Artificial Potential Fields

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The Influence of Opencast Lignite Mining Dehydration on Plant Production—A Methodological Study

Energies ◽

10.3390/en14071917 ◽

2021 ◽

Vol 14 (7) ◽

pp. 1917

Author(s):

Benedykt Pepliński ◽

Wawrzyniec Czubak

Keyword(s):

Brown Coal ◽

Crop Production ◽

Plant Production ◽

External Costs ◽

Opencast Mines ◽

Temporal And Spatial ◽

Potato Yields ◽

Burning Coal ◽

Depression Cone ◽

The Cost

In many circles, brown coal continues to be viewed as a cheap source of energy, resulting in numerous investments in new opencast brown coal mines. Such a perception of brown coal energy is only possible if the external costs associated with mining and burning coal are not considered. In past studies, external cost analysis has focused on the external costs of coal burning and associated emissions. This paper focuses on the extraction phase and assesses the external costs to agriculture associated with the resulting depression cone. This paper discusses the difficulties researchers face in estimating agricultural losses resulting from the development of a depression cone due to opencast mineral extraction. In the case of brown coal, the impacts are of a geological, natural-climatic, agricultural-productive, temporal, and spatial nature and result from a multiplicity of interacting factors. Then, a methodology for counting external costs in crop production was proposed. The next section estimates the external costs of crop production arising from the operation of opencast mines in the Konin-Turek brown coal field, which is located in central Poland. The analyses conducted showed a large decrease in grain and potato yields and no effect of the depression cone on sugar beet levels. Including the estimated external costs in the cost of producing electricity from mined brown coal would significantly worsen the profitability of that production.

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