Decision Support Tool for Operational Planning of Field Operations

Nilsson, René Søndergaard; Zhou, Kun

doi:10.3390/agronomy10020229

Cited by 8 publications

(5 citation statements)

References 19 publications

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“…If the headland width is unspecified, it is calculated based on the working width and machine turning radius. The outcome is a graph structure used for route generation or exporting lines to automatic guidance systems [28].…”

Section: System Operationmentioning

confidence: 99%

Robots for Forest Maintenance

Gameiro,

Pereira,

Viegas

et al. 2024

Forests

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Forest fires are becoming increasingly common, and they are devastating, fueled by the effects of global warming, such as a dryer climate, dryer vegetation, and higher temperatures. Vegetation management through selective removal is a preventive measure which creates discontinuities that will facilitate fire containment and reduce its intensity and rate of spread. However, such a method requires vast amounts of biomass fuels to be removed, over large areas, which can only be achieved through mechanized means, such as through using forestry mulching machines. This dangerous job is also highly dependent on skilled workers, making it an ideal case for novel autonomous robotic systems. This article presents the development of a universal perception, control, and navigation system for forestry machines. The selection of hardware (sensors and controllers) and data-integration and -navigation algorithms are central components of this integrated system development. Sensor fusion methods, operating using ROS, allow the distributed interconnection of all sensors and actuators. The results highlight the system’s robustness when applied to the mulching machine, ensuring navigational and operational accuracy in forestry operations. This novel technological solution enhances the efficiency of forest maintenance while reducing the risk exposure to forestry workers.

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Section: System Operationmentioning

confidence: 99%

Robots for Forest Maintenance

Gameiro,

Pereira,

Viegas

et al. 2024

Forests

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“…In this paper, we evaluated the efficiency of our method by considering area and distance indicators [44,45]. The corresponding results are presented in Table 5.…”

Section: Operation Efficiencymentioning

confidence: 99%

A Collaborative Path Planning Method for Intelligent Agricultural Machinery Based on Unmanned Aerial Vehicles

et al. 2023

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The development of agricultural farming has evolved from traditional agricultural machinery due to its efficiency and autonomy. Intelligent agricultural machinery is capable of autonomous driving and remote control, but due to its limited perception of farmland and field obstacles, the assistance of unmanned aerial vehicles (UAVs) is required. Although existing intelligent systems have greater advantages than traditional agricultural machinery in improving the quality of operations and reducing labor costs, they also produce complex operational planning problems. Especially as agricultural products and fields become more diversified, it is necessary to develop an adaptive operation planning method that takes into account the efficiency and quality of work. However, the existing operation planning methods lack practicality and do not guarantee global optimization because traditional planners only consider the path commands and generate the path in the rectangular field without considering other factors. To overcome these drawbacks, this paper proposes a novel and practical collaborative path planning method for intelligent agricultural machinery based on unmanned aerial vehicles. First, we utilize UAVs for obstacle detection. With the field information and operation data preprocessed, automatic agricultural machinery could be assisted in avoiding obstacles in the field. Second, by considering both the historical state of the current operation and the statistics from previous operations, the real-time control of agricultural machinery is determined. Therefore, the K-means algorithm is used to extract key control parameters and discretize the state space of agricultural machinery. Finally, the dynamic operation plan is established based on the Markov chain. This plan can estimate the probability of agricultural machinery transitioning from one state to another by analyzing data, thereby dynamically determining real-time control strategies. The field test with an automatic tractor shows that the operation planner can achieve higher performance than the other two popular methods.

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“…CPP has a wide range of applications in the field of robotics, such as planning paths for cleaner [2] or disinfecting robots [3], agriculture [4][5][6], rescue operations [7], airport pavement disease detection [8], etc. CPP-based software enables farmers to plan the field management operations and quantitatively evaluate different operational plans [9]. The CPP problem can be analyzed at several granularity levels.…”

Section: Introductionmentioning

confidence: 99%

Convolutional Neural Network-Based Approximation of Coverage Path Planning Results for Parking Lots

Kriščiūnas,

Čalnerytė,

Fyleris

et al. 2023

IJGI

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Parking lots have wide variety of shapes because of surrounding environment and the objects inside the parking lot, such as trees, manholes, etc. In the case of paving the parking lot, as much area as possible should be covered by the construction vehicle to reduce the need for manual workforce. Thus, the coverage path planning (CPP) problem is formulated. The CPP of the parking lots is a complex problem with constraints regarding various issues, such as dimensions of the construction vehicle and data processing time and resources. A strategy based on convolutional neural networks (CNNs) for the fast estimation of the CPP’s average track length, standard deviation of track lengths, and number of tracks was suggested in this article. Two datasets of different complexity were generated to analyze the suggested approach. The first case represented a simple case with a working polygon constructed out of several rectangles with applied shear and rotation transformations. The second case represented a complex geometry generated out of rectangles and ellipses, narrow construction area, and obstacles. The results were compared with the linear regression models, with the area of the working polygon as an input. For both generated datasets, the strategy to use an approximator to estimate outcomes led to more accurate results compared to the respective linear regression models. The suggested approach enables us to have rough estimates of a large number of geometries in a short period of time and organize the working process, for example, planning construction time and price, choosing the best decomposition of the working polygon, etc.

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Decision Support Tool for Operational Planning of Field Operations

Cited by 8 publications

References 19 publications

Robots for Forest Maintenance

Robots for Forest Maintenance

A Collaborative Path Planning Method for Intelligent Agricultural Machinery Based on Unmanned Aerial Vehicles

Convolutional Neural Network-Based Approximation of Coverage Path Planning Results for Parking Lots

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