Contributions to autonomous robust navigation of mobile robots in industrial applications

151 p.Un aspecto en el que las plataformas móviles actuales se quedan atrás en comparación con el punto que se ha alcanzado ya en la industria es la precisión. La cuarta revolución industrial trajo consigo la implantación de maquinaria en la mayor parte de procesos industriales, y una fortaleza de estos es su repetitividad. Los robots móviles autónomos, que son los que ofrecen una mayor flexibilidad, carecen de esta capacidad, principalmente debido al ruido inherente a las lecturas ofrecidas por los sensores y al dinamismo existente en la mayoría de entornos. Por este motivo, gran parte de este trabajo se centra en cuantificar el error cometido por los principales métodos de mapeado y localización de robots móviles,ofreciendo distintas alternativas para la mejora del posicionamiento.Asimismo, las principales fuentes de información con las que los robots móviles son capaces de realizarlas funciones descritas son los sensores exteroceptivos, los cuales miden el entorno y no tanto el estado del propio robot. Por esta misma razón, algunos métodos son muy dependientes del escenario en el que se han desarrollado, y no obtienen los mismos resultados cuando este varía. La mayoría de plataformas móviles generan un mapa que representa el entorno que les rodea, y fundamentan en este muchos de sus cálculos para realizar acciones como navegar. Dicha generación es un proceso que requiere de intervención humana en la mayoría de casos y que tiene una gran repercusión en el posterior funcionamiento del robot. En la última parte del presente trabajo, se propone un método que pretende optimizar este paso para así generar un modelo más rico del entorno sin requerir de tiempo adicional para ello

Adaptive Robotic Chassis (ARC)

The ARC is a width adjusting agricultural robot and accommodates auxiliary functions for supporting crop production and maintenance. Easily interchangeable payloads and components provide a modular solution to perform focused crop surveying functions with the potential for herbicide distribution, weeding, and harvesting while driving through varying crop rows. The potential auxiliary functions will be implemented by future teams with this year\u27s effort being put toward finishing the physical chassis. The final product was successfully designed to weigh approximately 600 pounds targeting rolling speeds of0.90 fps to 2.30 fps with proof of concept shown in testing consisting of chain drive attached to wheels to show speeds are attainable as well as bench tests to show differential control capabilities

A blokkláncon alapuló nyomonkövetési rendszerek alkalmazhatóságának elemzése szimulációs modellel az élelmiszer-ellátási láncban

Napjainkban a vásárlók fokozott egészség- és környezet tudatossága hatással van a fogyasztók élelmiszerekkel szemben támasztott igényeire, sokan kíváncsiak a termékek teljes életútjára. A korábban alkalmazott élelmiszer nyomonkövetési rendszerek is képesek ezeket az információkat előállítani, de a blokkláncok megjelenése új lehetőségeket nyithat meg ezen a területen is. A technológia innovációja nemcsak az információs aszimmetriát szüntetheti meg, hanem csökkentheti az élelmiszerbiztonsági kockázatokat is. Habár a fogyasztók a keresett információhoz könnyebben és gyorsabban juthatnak hozzá, az új blokklánc-alapú rendszer felállítása és üzemeltetési költsége növelheti a termékek árát. A rendelkezésre álló statisztikák és publikációk adatai alapján munkánk eredményeként egy rendszerdinamikai szimulációs modell készült el (az entitások áramának és tranzíciójának lekövetésével) a blokklánc-alapú nyomonkövetési rendszerek alkalmazhatóságának elemzésére. A modellen futtatott szimulációk szerint az új rendszert használó fogyasztók száma az elkövetkező öt évben nem éri el azt az arányt, ami gazdaságossá tenné a bevezetését. Tanulmányunkban ennek okait kerestük, illetve különféle hatásokat elemeztünk, amelyek befolyásolhatják a fogyasztókat

A model based method for evaluation of crop operation scenarios in greenhouses

Abstract This research initiated a model-based method to analyse labour in crop production systems and to quantify effects of system changes in order to contribute to effective greenhouse crop cultivation systems with efficient use of human labour and technology. This method was gradually given shape in the discrete event simulation model GWorkS, acronym for Greenhouse Work Simulation. Model based evaluation of labour in crop operations is relatively new in greenhouse horticulture and could allow for quantitative evaluation of existing greenhouse crop production systems, analysis of improvements, and identification of bottlenecks in crop operations. The modelling objective was a flexible and generic approach to quantify effects of production system changes. Cut-rose was selected as a case-study representative for many cut-flowers and fruit vegetables. The first focus was a queueing network model of the actions of a worker harvesting roses in a mobile cultivation system. Data and observations from a state-of-art mobile rose production system were used to validate and test the harvesting model. Model experiments addressed target values of operational parameters for best system performance. The model exposed effects of internal parameters not visible in acquired data. This was illustrated for operator and gutter speed as a function of crop yield. The structure and setup of the GWorkS model was generic where possible and system specific where inevitable. The generic concept was tested by transferring GWorkS to harvesting a greenhouse section in a static growing system for cut-roses and extending it with navigation in the greenhouse, product handling, and multiple operator activity (up to 3 workers). Also for rose harvesting in a static growing system, the model reproduced harvesting accurately. A seven workday validation for an average skilled harvester showed a relative root mean squared error (RRMSE) under 5% for both labour time and harvest rate. A validation for 96 days with various harvesters showed a higher RRMSE, 15.2% and 13.6% for labour time and harvest rate respectively. This increase was mainly caused by the absence of model parameters for individual harvesters. Work scenarios were simulated to examine effects of skill, equipment, and harvest management. For rose yields of 0.5 and 3 harvested roses per m2, harvest rate was 346 and 615 stems h-1 for average skilled harvesters, 207 and 339 stems h-1 for new harvesters and 407 and 767 stems h-1 for highly skilled harvesters. Economic effects of trolley choice are small, 0-2 € per 1000 stems and two harvest cycles per day was only feasible if yield quality effects compensate for extra costs of 0.2-1.1 eurocents per stem. In a sensitivity analysis and uncertainty analysis, parameters with strong influence on labour performance in harvesting roses in a static system were identified as well as effects of parameter uncertainty on key performance indicators. Differential sensitivity was analysed, and results were tested for linearity and superposability and verified using the robust Monte Carlo method. The model was not extremely sensitive for any of the 22 tested input parameters. Individual sensitivities changed with crop yield. Labour performance was most affected by greenhouse section dimensions, single rose cut time, and yield. Throughput was most affected by cut time of a single rose, yield, number of harvest cycles, greenhouse length and operator transport velocity. In uncertainty analysis the coefficient of variation for the most important outputs labour time and throughput is around 5%. The main sources of model uncertainty were in parallel execution of actions and trolley speed. The uncertainty effect of these parameters in labour time, throughput and utilisation of the operator is acceptably small with CV less than 5%. The combination of differential sensitivity analysis and Monte Carlo analysis gave full insight in both individual and total sensitivity of key performance indicators. To realise the objective of model based improvement of the operation of horticultural production systems in resources constrained system, the GWorkS-model was extended for simultaneous crop operations by multiple workers analysis. This objective was narrowed down to ranking eight scenarios with worker skill as a central theme including a labour management scenario applied in practise. The crop operations harvest, disbudding and bending were considered, which represent over 90% of crop-bound labour time. New sub-models on disbudding and bending were verified using measured data. The integrated scenario study on harvest, disbudding and bending showed differences between scenarios of up to 5 s per harvested rose in simulated labour time and up to 7.1 € m-2 per year in labour costs. The simulated practice of the grower and the scenario with minimum costs indicated possible savings of 4 € m-2 per year, which equals 15% of labour cost for harvest, disbudding and bending. Multi-factorial assessment of scenarios pointed out that working with low skilled, low paid workers is not effective. Specialised workers were most time effective with -17.5% compared to the reference, but overall a permanent team of skilled generalists ranked best. Reduced diversity in crop operations per day improved labour organisational outputs but ranked almost indifferent. The reference scenario was outranked by 5 scenarios. Discrete event simulation, as applied in the GWorkS-model, described greenhouse crop operations mechanistically correct and predicts labour use accurately. This model-based method was developed and validated by means of data sets originating from commercial growers. The model provided clear answers to research questions related to operations management and labour organisation using the full complexity of crop operations and a multi-factorial criterion. To the best of our knowledge, the GWorkS-model is the first model that is able to simulate multiple crop operations with constraints on available staff and resources. The model potentially supports analysis and evaluation of design concepts for system innovation.</p

A review on multi-robot systems: current challenges for operators and new developments of interfaces

[ES] Los sistemas multi-robot están experimentando un gran desarrollo en los últimos tiempos, ya que mejoran el rendimiento de las misiones actuales y permiten realizar nuevos tipos de misiones. Este artículo analiza el estado del arte de los sistemas multi-robot, abordando un conjunto de temas relevantes: misiones, flotas, operadores, interacción humano-sistema e interfaces. La revisión se centra en los retos relacionados con factores humanos como la carga de trabajo o la conciencia de la situación, así como en las propuestas de interfaces adaptativas e inmersivas para solucionarlos.[EN] Multi-robot systems are experiencing great development in recent times, since they are improving the performance of current missions and allowing new types of missions. This article analyzes the state of the art of multi-robot systems, addressing a set of relevant topics: missions, fleets, operators, human-system interaction and interfaces. The review focuses on the challenges related to human factors such as workload and situational awareness, as well as the proposals of adaptive and immersive interfaces to solve them.Esta investigación ha recibido fondos de los proyectos SAVIER (Situational Awareness VIrtual EnviRonment) de Airbus; RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub, S2018/ NMT-4331, financiado por los Programas de Actividades I+D de la Comunidad de Madrid y confinanciado por los Fondos Estructurales de la UE; y DPI2014-56985-R (Protección Robotizada de Infraestructuras Críticas) financiado por el ministerio de Economía y Competitividad del Gobierno de España.Roldan-Gómez, JJ.; De León Rivas, J.; Garcia-Aunon, P.; Barrientos, A. (2020). Una revisión de los sistemas multi-robot: desafíos actuales para los operadores y nuevos desarrollos de interfaces. 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