scholarly journals ARENA—Augmented Reality to Enhanced Experimentation in Smart Warehouses

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4308 ◽  
Author(s):  
Luis Piardi ◽  
Vivian Cremer Kalempa ◽  
Marcelo Limeira ◽  
André Schneider de Oliveira ◽  
Paulo Leitão
Keyword(s):  
Augmented Reality ◽  
New Technologies ◽  
Small Scale ◽  
Robot Perception ◽  
Novel Approach ◽  
Swarm Robots ◽  
Robot Systems ◽  
Laser Range Finders ◽  
Manufacturing Productivity ◽  
Real Scenario

The current industrial scenario demands advances that depend on expensive and sophisticated solutions. Augmented Reality (AR) can complement, with virtual elements, the real world. Faced with this features, an AR experience can meet the demand for prototype testing and new solutions, predicting problems and failures that may only exist in real situations. This work presents an environment for experimentation of advanced behaviors in smart factories, allowing experimentation with multi-robot systems (MRS), interconnected, cooperative, and interacting with virtual elements. The concept of ARENA introduces a novel approach to realistic and immersive experimentation in industrial environments, aiming to evaluate new technologies aligned with the Industry 4.0. The proposed method consists of a small-scale warehouse, inspired in a real scenario characterized in this paper, managing by a group of autonomous forklifts, fully interconnected, which are embodied by a swarm of tiny robots developed and prepared to operate in the small scale scenario. The AR is employed to enhance the capabilities of swarm robots, allowing box handling and virtual forklifts. Virtual laser range finders (LRF) are specially designed as segmentation of a global RGB-D camera, to improve robot perception, allowing obstacle avoidance and environment mapping. This infrastructure enables the evaluation of new strategies to improve manufacturing productivity, without compromising the production by automation faults.

scholarly journals Multi-Robot Preemptive Task Scheduling with Fault Recovery: A Novel Approach to Automatic Logistics of Smart Factories

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6536
Author(s):  
Vivian Cremer Kalempa ◽  
Luis Piardi ◽  
Marcelo Limeira ◽  
André Schneider de Oliveira
Keyword(s):  
Augmented Reality ◽  
Task Scheduling ◽  
Task Allocation ◽  
Autonomous Robots ◽  
Small Scale ◽  
Fault Recovery ◽  
Novel Approach ◽  
Robot Task ◽  
Smart Factories ◽  
Multi Robot

This paper presents a novel approach for Multi-Robot Task Allocation (MRTA) that introduces priority policies on preemptive task scheduling and considers dependencies between tasks, and tolerates faults. The approach is referred to as Multi-Robot Preemptive Task Scheduling with Fault Recovery (MRPF). It considers the interaction between running processes and their tasks for management at each new event, prioritizing the more relevant tasks without idleness and latency. The benefit of this approach is the optimization of production in smart factories, where autonomous robots are being employed to improve efficiency and increase flexibility. The evaluation of MRPF is performed through experimentation in small-scale warehouse logistics, referred to as Augmented Reality to Enhanced Experimentation in Smart Warehouses (ARENA). An analysis of priority scheduling, task preemption, and fault recovery is presented to show the benefits of the proposed approach.

scholarly journals Fully Automated Cultivation of Adipose-Derived Stem Cells in the StemCellDiscovery—A Robotic Laboratory for Small-Scale, High-Throughput Cell Production Including Deep Learning-Based Confluence Estimation

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 575
Author(s):  
Jelena Ochs ◽  
Ferdinand Biermann ◽  
Tobias Piotrowski ◽  
Frederik Erkens ◽  
Bastian Nießing ◽  
...  
Keyword(s):  
Stem Cells ◽  
Deep Learning ◽  
High Throughput ◽  
High Speed ◽  
New Technologies ◽  
Human Mesenchymal Stem Cells ◽  
Simulation Software ◽  
System Capacity ◽  
Small Scale ◽  
Production Environment

Laboratory automation is a key driver in biotechnology and an enabler for powerful new technologies and applications. In particular, in the field of personalized therapies, automation in research and production is a prerequisite for achieving cost efficiency and broad availability of tailored treatments. For this reason, we present the StemCellDiscovery, a fully automated robotic laboratory for the cultivation of human mesenchymal stem cells (hMSCs) in small scale and in parallel. While the system can handle different kinds of adherent cells, here, we focus on the cultivation of adipose-derived hMSCs. The StemCellDiscovery provides an in-line visual quality control for automated confluence estimation, which is realized by combining high-speed microscopy with deep learning-based image processing. We demonstrate the feasibility of the algorithm to detect hMSCs in culture at different densities and calculate confluences based on the resulting image. Furthermore, we show that the StemCellDiscovery is capable of expanding adipose-derived hMSCs in a fully automated manner using the confluence estimation algorithm. In order to estimate the system capacity under high-throughput conditions, we modeled the production environment in a simulation software. The simulations of the production process indicate that the robotic laboratory is capable of handling more than 95 cell culture plates per day.

An Innovation System for Building Manufacturing

2012 ◽  
Author(s):  
Flávio Craveiro ◽  
João Meneses de Matos ◽  
Helena Bártolo ◽  
Paulo Bártolo
Keyword(s):  
New Technologies ◽  
Innovation System ◽  
Efficient Solutions ◽  
Urban Environments ◽  
Functionally Graded ◽  
Functional Requirements ◽  
Geometric Information ◽  
Material Deposition ◽  
Novel Approach ◽  
Graded Material

Traditionally the construction sector is very conservative, risk averse and reluctant to adopt new technologies and ideas. The construction industry faces great challenges to develop more innovative and efficient solutions. In recent years, significant advances in technology and more sustainable urban environments has been creating numerous opportunities for innovation in automation. This paper proposes a new system based on extrusion-based technologies aiming at solving some limitations of current technologies to allow a more efficient building construction with organic forms and geometries, based on sustainable eco principles. This novel approach is described through a control deposition software. Current modeling techniques focus only on capturing the geometric information and cannot satisfy the requirements from modeling the components made of multi-heterogeneous materials. There is a great deal of interest in tailoring structures so the functional requirements can vary with location. The proposed functionally graded material deposition (FGM) system will allow a smooth variation of material properties to build up more efficient buildings regarding thermal, acoustic and structural conditions.

A Novel Approach With Bayesian Networks to Multi-Robot Task Allocation in Dynamic Environments

2021 ◽  
Author(s):  
Ching-Wei Chuang ◽  
Harry H. Cheng
Keyword(s):  
Bayesian Networks ◽  
Task Allocation ◽  
Low Cost ◽  
Dynamic Environments ◽  
Modern World ◽  
Robot System ◽  
Novel Approach ◽  
Robot Systems ◽  
Robot Task ◽  
Multi Robot

Abstract In the modern world, building an autonomous multi-robot system is essential to coordinate and control robots to help humans because using several low-cost robots becomes more robust and efficient than using one expensive, powerful robot to execute tasks to achieve the overall goal of a mission. One research area, multi-robot task allocation (MRTA), becomes substantial in a multi-robot system. Assigning suitable tasks to suitable robots is crucial in coordination, which may directly influence the result of a mission. In the past few decades, although numerous researchers have addressed various algorithms or approaches to solve MRTA problems in different multi-robot systems, it is still difficult to overcome certain challenges, such as dynamic environments, changeable task information, miscellaneous robot abilities, the dynamic condition of a robot, or uncertainties from sensors or actuators. In this paper, we propose a novel approach to handle MRTA problems with Bayesian Networks (BNs) under these challenging circumstances. Our experiments exhibit that the proposed approach may effectively solve real problems in a search-and-rescue mission in centralized, decentralized, and distributed multi-robot systems with real, low-cost robots in dynamic environments. In the future, we will demonstrate that our approach is trainable and can be utilized in a large-scale, complicated environment. Researchers might be able to apply our approach to other applications to explore its extensibility.

scholarly journals Energy Production from Biogas: Competitiveness and Support Instruments in Latvia

2016 ◽  
Vol 53 (5) ◽  
pp. 43-53
Author(s):  
G. Klāvs ◽  
A. Kundziņa ◽  
I. Kudrenickis
Keyword(s):  
New Technologies ◽  
Local Economic Development ◽  
Renewable Energy Sources ◽  
Distribution Network ◽  
Scale Up ◽  
Electricity Production ◽  
Small Scale ◽  
Gas Distribution ◽  
Ex Post ◽  
The Impact

Abstract Use of renewable energy sources (RES) might be one of the key factors for the triple win-win: improving energy supply security, promoting local economic development, and reducing greenhouse gas emissions. The authors ex-post evaluate the impact of two main support instruments applied in 2010-2014 – the investment support (IS) and the feed-in tariff (FIT) – on the economic viability of small scale (up to 2MWel) biogas unit. The results indicate that the electricity production cost in biogas utility roughly corresponds to the historical FIT regarding electricity production using RES. However, if in addition to the FIT the IS is provided, the analysis shows that the practice of combining both the above-mentioned instruments is not optimal because too high total support (overcompensation) is provided for a biogas utility developer. In a long-term perspective, the latter gives wrong signals for investments in new technologies and also creates unequal competition in the RES electricity market. To provide optimal biogas utilisation, it is necessary to consider several options. Both on-site production of electricity and upgrading to biomethane for use in a low pressure gas distribution network are simulated by the cost estimation model. The authors’ estimates show that upgrading for use in a gas distribution network should be particularly considered taking into account the already existing infrastructure and technologies. This option requires lower support compared to support for electricity production in small-scale biogas utilities.

scholarly journals UX in AR-Supported Industrial Human–Robot Collaborative Tasks: A Systematic Review

2021 ◽  
Vol 11 (21) ◽  
pp. 10448
Author(s):  
Riccardo Karim Khamaisi ◽  
Elisa Prati ◽  
Margherita Peruzzini ◽  
Roberto Raffaeli ◽  
Marcello Pellicciari
Keyword(s):  
Augmented Reality ◽  
Industrial Revolution ◽  
New Technologies ◽  
Recent Literature ◽  
Modern Human ◽  
Assessment Procedure ◽  
Functional Requirements ◽  
Collaborative Robotics ◽  
Fourth Industrial Revolution ◽  
Standardization Process

The fourth industrial revolution is promoting the Operator 4.0 paradigm, originating from a renovated attention towards human factors, growingly involved in the design of modern, human-centered processes. New technologies, such as augmented reality or collaborative robotics are thus increasingly studied and progressively applied to solve the modern operators’ needs. Human-centered design approaches can help to identify user’s needs and functional requirements, solving usability issues, or reducing cognitive or physical stress. The paper reviews the recent literature on augmented reality-supported collaborative robotics from a human-centered perspective. To this end, the study analyzed 21 papers selected after a quality assessment procedure and remarks the poor adoption of user-centered approaches and methodologies to drive the development of human-centered augmented reality applications to promote an efficient collaboration between humans and robots. To remedy this deficiency, the paper ultimately proposes a structured framework driven by User eXperience approaches to design augmented reality interfaces by encompassing previous research works. Future developments are discussed, stimulating fruitful reflections and a decisive standardization process.

scholarly journals Tracking the Maturity of Industry 4.0: The Perspective of a Real Scenario

2021 ◽  
Author(s):  
Vítor Alcácer ◽  
Carolina Rodrigues ◽  
Helena Carvalho ◽  
Virgilio Cruz-Machado
Keyword(s):  
Empirical Data ◽  
Industry 4.0 ◽  
Business Models ◽  
New Technologies ◽  
Industrial Cluster ◽  
Academic Community ◽  
Enabling Technologies ◽  
Readiness Level ◽  
Different Dimensions ◽  
Real Scenario

Abstract In order to track industry 4.0 status, readiness models can be used to analyze the state of indus-try 4.0 technologies’ implementation allowing the quantification and qualification of its readiness level, focusing on different dimensions. To this matter, there are companies unable to relate the industry 4.0 with their business models, leading to a lack of a correct self-assess in order to understand the reached readiness level. Not all companies are adopting these new technologies with the same ease and with the same pace. Into this purpose, it is important to understand how to assess the industry 4.0’ readiness so far and what are the barriers on the adoption of these enabling technologies by the industry. This paper aims to assess the industry 4.0’ readiness level of companies, understand the perception of companies due to the barriers on the adoption of industry 4.0 enabling technologies and bring new barriers for discussion on academic community. To this end, empirical data was collected on a sample of 15 companies belonging to an important industrial cluster in Portugal.

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