Mix-opt: A new route operator for optimal coverage path planning for a fleet in an agricultural environment

Conesa-Muñoz, Jesús; Pajares, Gonzalo; Ribeiro, Ángela

doi:10.1016/j.eswa.2015.12.047

Cited by 68 publications

(39 citation statements)

References 19 publications

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“…Efficient management of paths and routes for teams of autonomous off-road vehicles is crucial for challenging robotic applications such as planetary exploration [11], agriculture [4], and search and rescue (SAR) in post-disaster situations [6]. In off-road environments, the absence of pre-defined roads results in a much larger search space, and terrain characteristics, such as gradient, affect vehicle mobility in aspects such as navigability, travel time or energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Velocity-Based Heuristic Evaluation for Path Planning and Vehicle Routing for Victim Assistance in Disaster Scenarios

Toscano-Moreno

Mandow

Martínez

et al. 2019

Advances in Intelligent Systems and Computing

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Natural and human-made disasters require effective victim assistance and last-mile relief supply operations with teams of ground vehicles. In these applications, digital elevation models (DEM) can provide accurate knowledge for safe vehicle motion planning but grid representation results in very large search graphs. Furthermore, travel time, which becomes a crucial cost optimization criterion, may be affected by inclination and other challenging terrain characteristics. In this paper, our goal is to evaluate a search heuristic function based on anisotropic vehicle velocity restrictions for building the cost matrix required for multi-vehicle routing on natural terrain and disaster sites. The heuristic is applied to compute the fastest travel times between every pair of matrix elements by means of a path planning algorithm. The analysis is based on a case study on the ortophotographic-based DEM of natural terrain with different target points, where the proposed heuristic is compared against an exhaustive search solution.

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Section: Introductionmentioning

confidence: 99%

Velocity-Based Heuristic Evaluation for Path Planning and Vehicle Routing for Victim Assistance in Disaster Scenarios

Toscano-Moreno

Mandow

Martínez

et al. 2019

Advances in Intelligent Systems and Computing

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“…In contrast to route planning methods such as in Conesa-Muñoz et al (2016b) for the in-field operation of a fleet of vehicles, the presented method focuses on the in-field operation of a single vehicle that is repeatedly returning to the field entrance for refilling. This is primarily motivated by the targeted crops (wheat, rapeseed and barley) and the costs of corresponding agricultural vehicles.…”

Section: Introductionmentioning

confidence: 99%

Partial field coverage based on two path planning patterns

Plessen

2018

Biosystems Engineering

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“…Inspired from the literature about "coverage path planning" [14,[15][16][17], it would be interesting to consider if capacitated vehicle routing problem models could bring added value in the remediation work, in the case of soil excavation by heavy equipment.…”

Section: Improvements and Future Developmentmentioning

confidence: 99%

“…In the case of ex-situ 2 remediation, literature does not mention the use of navigation and positioning technologies for the excavation work done by heavy machineries. As positioning technologies are routinely employed in civil engineering and agriculture [14,[15][16][17][18] for the guidance of heavy equipment for precise and efficient work it seems the shortcomings in the case of ex-situ remediation lays in the capacity to generate adequate remediation plans and in the lack of adapted GIS tools, models, methods and practice [19]. In response, this work develops models in order to be able to produce a plan containing "clean-up parcels" and derived navigation data.…”

Section: Introductionmentioning

confidence: 99%

Development and testing of geo-processing models for the automatic generation of remediation plan and navigation data to use in industrial disaster remediation

Lucas

Lénárt

Solymosi

2016

Open geospatial data, softw. stand.

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Background: This paper introduces research done on the automatic preparation of remediation plans and navigation data for the precise guidance of heavy machinery in clean-up work after an industrial disaster. The input test data consists of a pollution extent shapefile derived from the processing of hyperspectral aerial survey data from the Kolontár red mud disaster. Methods: Five algorithms were developed, the respective scripts were written in Python, and then tested. The first model aims at drawing a parcel clean-up plan. It tests four different parcel orientations (0, 90, 45 and 135°) and keeps the plan where clean-up parcels are less numerous. The second model uses the orientation of each contamination polygon feature to orientate the features of the clean-up plan accordingly. The third model tested if it is worth rotating the parcel features by 90°for some contamination feature. The fourth model drifts the clean-up parcel of a work plan following a grid pattern; here also with the belief to reduce the final number of parcel features. The last model aims at drawing a navigation line in the middle of each clean-up parcel. Results: The best optimization results were achieved with the second model; the drift and 90°rotation models do not offer significant advantage. By comparison of the results between different orientations we demonstrated that the number of clean-up parcels generated varies in a range of 4 to 38 % from plan to plan. Conclusions: Such a significant variation with the resulting feature numbers shows that the optimal orientation identification can result in saving work, time and money in remediation.

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Mix-opt: A new route operator for optimal coverage path planning for a fleet in an agricultural environment

Cited by 68 publications

References 19 publications

Velocity-Based Heuristic Evaluation for Path Planning and Vehicle Routing for Victim Assistance in Disaster Scenarios

Velocity-Based Heuristic Evaluation for Path Planning and Vehicle Routing for Victim Assistance in Disaster Scenarios

Partial field coverage based on two path planning patterns

Development and testing of geo-processing models for the automatic generation of remediation plan and navigation data to use in industrial disaster remediation

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