Model-Based Development of a Multi-algorithm Harvest Planning System

Couto, Luís Diogo; Tran-Jørgensen, Peter W. V.; Edwards, Gareth

doi:10.1007/978-3-319-69832-8_2

Cited by 3 publications

(6 citation statements)

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“…Our architecture is built on top of a prototype reported in previous publications. In [4,5], the authors reported on how optimisation algorithms for different aspects of the harvest operation can be combined through the usage of a combination of design patterns and a formal Vienna developed method (VDM) model. This paper is based on the same model, but we added the deviation mechanism to allow replanning, and ensure the plan is updated throughout the whole harvest process.…”

Section: Related Workmentioning

confidence: 99%

“…The VDM++ model supports both off-line simulation and real-time guidance of harvest operations, so it is rather complex, but in here we report on the core functionality needed to understand the deviation listings only. For a thorough description of the model, the many previous publications should suffice [4][5][6][7]. The model is object oriented, and its class diagram is shown in Figure 8.…”

Section: Existing Vdm++ Modelmentioning

confidence: 99%

“…As shown in Table 1, the execution time of the final test was approximately one hour. In comparison, the runtime of the simulation for the same field was less than 60 s (For more details about the runtime of simulations see [4][5][6]), but this simulation did not include any deviations or triggering of such and did therefore not test the HCA. Injection of deviations in the simulation tool could improve testing of the HCA while reducing testing time and cost significantly, as initial tests could be carried out in a virtual setting rather than in the field with licensed operators and real machinery.…”

Section: Simulation Runtime Vs In Field Testingmentioning

confidence: 99%

“…which deploys an initial harvest plan tuned for a best case scenario in terms of the field conditions. The execution level was previously developed as reported in [4][5][6][7], and, before our additions, implemented a stepwise loop reading the values for the several vehicle parameters (e.g., GPS position, bin level) in the field and issuing the routes to be shown to the operators in thin clients to be carried in cabins of the vehicles.…”

Section: Introductionmentioning

confidence: 99%

“…The method prescribes the development of state-based and object-oriented models in the VDM formal modelling language and has been previously extensively applied in the development of high-level controllers. The HLS model implements a stepwise loop which, for clarity, in this section, is described in terms of a feedback loop in the notation of control systems and we refer the reader interested in the VDM details to [4][5][6] and in Section 6.…”

mentioning

confidence: 99%

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The Harvest Coach Architecture: Embedding Deviation-Tolerance in a Harvest Logistic Solution

2019

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We introduce a deviation-tolerance software architecture, which is devised for a prototype of a cloud-based harvest operation optimisation system issuing harvest plans. The deviation-tolerance architecture adapts the fault tolerance notions originating in the area of systems engineering to the harvest domain and embeds them into the Vienna developed method (VDM) model at the core of our harvest logistics system prototype. The fault tolerance supervision/execution level architecture is framed under the notion of an “harvest coach” which diagnoses deviations to the planned operations using “harvest deviation monitors” and deploys a novel “plan” (controller) that mitigates the encountered “deviation” (fault). The architecture enabled the early start of field experiments of the harvest logistics system prototype, which lead to the validation/refutation of early design stage assumptions on the diverse system components behaviours and capabilities. For instance, we casually found discrepancies in the arithmetic precision of open-source libraries used in the conversion of vehicle positioning coordinates, we assessed the maturity of the frameworks used to develop the field user interfaces, and we calibrated the level of system-operator interactivity when deviations occurs. The obtained results indicate that the architecture may have a positive impact in the context of developing systems featuring intrinsic human-driven deviations which require mitigation.

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Section: Related Workmentioning

confidence: 99%