Autonomous Navigation Module for Tracked Compost Turners

Reitbauer, Eva Maria; Schmied, Christoph; Wieser, Manfred

doi:10.23919/enc48637.2020.9317465

Cited by 9 publications

(5 citation statements)

References 4 publications

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“…The process of turning the windrows is carried out by compost turners. In addition to traditional technologies, research is currently being conducted on a fully autonomous, electric compost turner as part of international research projects at the Graz University of Technology [20][21][22][23]. A prototype is shown in Figure 1.…”

Section: Sharing Concepts and Compostingmentioning

confidence: 99%

Development of a Sharing Concept for Industrial Compost Turners Using Model-Based Systems Engineering, under Consideration of Technical and Logistical Aspects

2022

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The trend of sharing concepts is constantly increasing, whether this may be for economic or environmental reasons. Consequently, numerous scientific research works have addressed the subject of sharing concepts. Many of these works have dealt with questions on the topic of sharing concepts itself, however, much less research has been dedicated to the question of how the sharing concept can be developed in the very first place. Thus, the purpose of this work was to systematically use systems engineering methods to develop a sharing concept for heavy-duty agricultural vehicles, while having a strong focus on technical and logistical aspects. Due to the multidisciplinary complexity of the sharing concept, a method from the field of model-based systems engineering, ARCADIA, was chosen. On ARCADIA’s top level, operational analysis was carried out to identify the key stakeholders. The next level, systems analysis, showed that the sharing model can be divided into three main processes: (1) data acquisition and preparation; (2) location planning; (3) and route planning. For these main processes, corresponding methods, algorithms and models were sought and compared against each other in the last level, logical analysis. It can be concluded that the ARCADIA method has provided a framework for evaluating the correlations and interrelationships between methods, algorithms and models at different levels to develop a sharing concept for compost turners from a technical perspective.

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Section: Sharing Concepts and Compostingmentioning

confidence: 99%

Development of a Sharing Concept for Industrial Compost Turners Using Model-Based Systems Engineering, under Consideration of Technical and Logistical Aspects

2022

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“…It is possible to reduce the uncertainty of the reference position by adding a second RTS to track the same prism. Reitbauer et al [14] have used a second RTS to follow two different prisms on a compost turner, enabling the measurement of four DOFs on the platform (i.e., the position and the yaw angle). To obtain the full pose reference of a static robotic platform, it is possible to manually measure three prisms with a single RTS [3].…”

Section: Related Workmentioning

confidence: 99%

Accurate outdoor ground truth based on total stations

Vaidis¹,

Giguère²,

Pomerleau³

et al. 2021

2021 18th Conference on Robots and Vision (CRV)

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In the context of robotics, accurate ground truth positioning is essential for the development of Simultaneous Localization and Mapping (SLAM) and control algorithms. Robotic Total Stations (RTSs) provide accurate and precise reference positions in different types of outdoor environments, especially when compared to the limited accuracy of Global Navigation Satellite System (GNSS) in cluttered areas. Three RTSs give the possibility to obtain the six-Degrees Of Freedom (DOF) reference pose of a robotic platform. However, the uncertainty of every pose is rarely computed for trajectory evaluation. As evaluation algorithms are getting increasingly precise, it becomes crucial to take into account this uncertainty. We propose a method to compute this six-DOF uncertainty from the fusion of three RTSs based on Monte Carlo (MC) methods. This solution relies on point-to-point minimization to propagate the noise of RTSs on the pose of the robotic platform. Five main noise sources are identified to model this uncertainty: noise inherent to the instrument, tilt noise, atmospheric factors, time synchronization noise, and extrinsic calibration noise. Based on extensive experimental work, we compare the impact of each noise source on the prism uncertainty and the final estimated pose. Tested on more than 50 km of trajectories, our comparison highlighted the importance of the calibration noise and the measurement distance, which should be ideally under 75 m. Moreover, it has been noted that the uncertainty on the pose of the robot is not prominently affected by one particular noise source, compared to the others.

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“…To overcome these difficulties, the TU Graz and its partners are currently working intensively on solutions, both on aspects of the mechanical engineering domain (development of a fully autonomous electric compost turner, see Figure 1) and on conceptual solutions [25][26][27][28][29]. Our previous work addressed the basic ideas of a sharing platform for compost turners and can thus be considered as a first footstep in this field [30,31].…”

Section: Introductionmentioning

confidence: 99%

Hyperconnected Logistic Platform for Heavy-Duty Machinery: Leveraging Physical Internet Principles to Drive the Composting Industry

Cichocki,

Barenji,

Montreuil

et al. 2023

Sustainability

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The Physical Internet (PI) envisions a global logistics system that integrates physical, digital and operational connections. This study aims to develop a hyperconnected logistic platform for heavy-duty machinery (HDM) in the composting industry by utilizing a systematic methodology. The proposed architecture consists of four layers: the Domain Model, the MBSE Model, the Information Sharing Model and the Agent-based Simulation Platform. The Domain Model analyzes the current situation and investigates stakeholder viewpoints, and the MBSE Model reduces complexity and describes mutual interactions between requirements and needs. The Information Sharing Model focuses on the information exchange among the main components, and the Agent-based Simulation Platform implements the proposed platform. The feasibility of the proposed architecture is demonstrated through a use case in Styria, Austria. Three simulation-based scenarios are analyzed, starting from the semi-hyperconnected approach up to the hyperconnected approach with PI vision integration. The results indicate that the hyperconnected platform is successful in serving all composting facilities, leveraging underutilized resources and promoting high-quality compost production. Thus, the platform provides support in a local, communal setting, resulting in enhancing the circular economy within the composting sector. Our efforts aim to contribute to the realization of the Physical Internet vision and promote composting to ultimately achieve a more sustainable future.

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Autonomous Navigation Module for Tracked Compost Turners

Cited by 9 publications

References 4 publications

Development of a Sharing Concept for Industrial Compost Turners Using Model-Based Systems Engineering, under Consideration of Technical and Logistical Aspects

Development of a Sharing Concept for Industrial Compost Turners Using Model-Based Systems Engineering, under Consideration of Technical and Logistical Aspects

Accurate outdoor ground truth based on total stations

Hyperconnected Logistic Platform for Heavy-Duty Machinery: Leveraging Physical Internet Principles to Drive the Composting Industry

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