377 research outputs found
Experimental analysis of using radar as an extrinsic sensor for human-robot collaboration
Collaborative robots are expected to be an integral part of driving the fourth industrial revolution that is soon expected to happen. In human-robot collaboration, the robot and a human share a common workspace and work on a common task. Here the safety of a human working with the robot is of utmost importance. A collaborative robot usually consists of various sensors to ensure the safety of a human working with the robot. This research mainly focuses on establishing a safe environment for a human working alongside a robot by mounting an FMCW radar as an extrinsic sensor, through which the workspace of the robot is monitored. A customized tracking algorithm is developed for the sensor used in this study by including a dynamically varying gating threshold, and information about consecutive missed detections to track and localize the human around the workspace of the robot. The performance of the proposed system in successfully establishing a safe human-robot collaboration is examined across a few scenarios that arise when a single human operator is working alongside a robot, with the radar operating in different modes. An OptiTrack Motion Capture System is used as ground truth to validate the efficacy of the proposed system
Occupational health and safety issues in human-robot collaboration: State of the art and open challenges
Human-Robot Collaboration (HRC) refers to the interaction of workers and robots in a shared workspace. Owing to the integration of the industrial automation strengths with the inimitable cognitive capabilities of humans, HRC is paramount to move towards advanced and sustainable production systems. Although the overall safety of collaborative robotics has increased over time, further research efforts are needed to allow humans to operate alongside robots, with awareness and trust. Numerous safety concerns are open, and either new or enhanced
technical, procedural and organizational measures have to be investigated to design and implement inherently safe and ergonomic automation solutions, aligning the systems performance and the human safety. Therefore, a bibliometric analysis and a literature review are carried out in the present paper to provide a comprehensive overview of Occupational Health and Safety (OHS) issues in HRC. As a result, the most researched topics and application areas, and the possible future lines of research are identified. Reviewed articles stress the central role
played by humans during collaboration, underlining the need to integrate the human factor in the hazard analysis and risk assessment. Human-centered design and cognitive engineering principles also require further investigations to increase the worker acceptance and trust during collaboration. Deepened studies are compulsory in the healthcare sector, to investigate the social and ethical implications of HRC. Whatever the application context is, the implementation of more and more advanced technologies is fundamental to overcome the current HRC safety concerns, designing low-risk HRC systems while ensuring the system productivity
Machine Learning Based Object Classification and Identification Scheme Using an Embedded Millimeter-Wave Radar Sensor
ABSTRACT: A target’s movements and radar cross sections are the key parameters to consider when designing a radar sensor for a given application. This paper shows the feasibility and effectiveness of using 24 GHz radar built-in low-noise microwave amplifiers for detecting an object. For this purpose a supervised machine learning model (SVM) is trained using the recorded data to classify the targets based on their cross sections into four categories. The trained classifiers were used to classify the objects with varying distances from the receiver. The SVM classification is also compared with three methods based on binary classification: a one-against-all classification, a one-against-one classification, and a directed acyclic graph SVM. The level of accuracy is approximately 96.6%, and an F1-score of 96.5% is achieved using the one-against-one SVM method with an RFB kernel. The proposed contactless radar in combination with an SVM algorithm can be used to detect and categorize a target in real time without a signal processing toolbox
one6G white paper, 6G technology overview:Second Edition, November 2022
6G is supposed to address the demands for consumption of mobile networking services in 2030 and beyond. These are characterized by a variety of diverse, often conflicting requirements, from technical ones such as extremely high data rates, unprecedented scale of communicating devices, high coverage, low communicating latency, flexibility of extension, etc., to non-technical ones such as enabling sustainable growth of the society as a whole, e.g., through energy efficiency of deployed networks. On the one hand, 6G is expected to fulfil all these individual requirements, extending thus the limits set by the previous generations of mobile networks (e.g., ten times lower latencies, or hundred times higher data rates than in 5G). On the other hand, 6G should also enable use cases characterized by combinations of these requirements never seen before, e.g., both extremely high data rates and extremely low communication latency). In this white paper, we give an overview of the key enabling technologies that constitute the pillars for the evolution towards 6G. They include: terahertz frequencies (Section 1), 6G radio access (Section 2), next generation MIMO (Section 3), integrated sensing and communication (Section 4), distributed and federated artificial intelligence (Section 5), intelligent user plane (Section 6) and flexible programmable infrastructures (Section 7). For each enabling technology, we first give the background on how and why the technology is relevant to 6G, backed up by a number of relevant use cases. After that, we describe the technology in detail, outline the key problems and difficulties, and give a comprehensive overview of the state of the art in that technology. 6G is, however, not limited to these seven technologies. They merely present our current understanding of the technological environment in which 6G is being born. Future versions of this white paper may include other relevant technologies too, as well as discuss how these technologies can be glued together in a coherent system
Large space structures and systems in the space station era: A bibliography with indexes
Bibliographies and abstracts are listed for 1219 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1, 1990 and December 31, 1990. The purpose is to provide helpful information to the researcher, manager, and designer in technology development and mission design according to system, interactive analysis and design, structural and thermal analysis and design, structural concepts and control systems, electronics, advanced materials, assembly concepts, propulsion, and solar power satellite systems
A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks
The fifth generation (5G) mobile networks are envisaged to enable a plethora
of breakthrough advancements in wireless technologies, providing support of a
diverse set of services over a single platform. While the deployment of 5G
systems is scaling up globally, it is time to look ahead for beyond 5G systems.
This is driven by the emerging societal trends, calling for fully automated
systems and intelligent services supported by extended reality and haptics
communications. To accommodate the stringent requirements of their prospective
applications, which are data-driven and defined by extremely low-latency,
ultra-reliable, fast and seamless wireless connectivity, research initiatives
are currently focusing on a progressive roadmap towards the sixth generation
(6G) networks. In this article, we shed light on some of the major enabling
technologies for 6G, which are expected to revolutionize the fundamental
architectures of cellular networks and provide multiple homogeneous artificial
intelligence-empowered services, including distributed communications, control,
computing, sensing, and energy, from its core to its end nodes. Particularly,
this paper aims to answer several 6G framework related questions: What are the
driving forces for the development of 6G? How will the enabling technologies of
6G differ from those in 5G? What kind of applications and interactions will
they support which would not be supported by 5G? We address these questions by
presenting a profound study of the 6G vision and outlining five of its
disruptive technologies, i.e., terahertz communications, programmable
metasurfaces, drone-based communications, backscatter communications and
tactile internet, as well as their potential applications. Then, by leveraging
the state-of-the-art literature surveyed for each technology, we discuss their
requirements, key challenges, and open research problems
Internet of Robotic Things Intelligent Connectivity and Platforms
The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and “things” have evolved significantly. “Things” now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of “intelligent things” (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.publishedVersio
Next Generation Auto-Identification and Traceability Technologies for Industry 5.0: A Methodology and Practical Use Case for the Shipbuilding Industry
[Abstract] Industry 5.0 follows the steps of the Industry 4.0 paradigm and seeks for revolutionizing the way industries operate. In fact, Industry 5.0 focuses on research and innovation to support industrial production sustainability and place the well-being of industrial workers at the center of the production process. Thus, Industry 5.0 relies on three pillars: it is human-centric, it encourages sustainability and it is aimed at developing resilience against disruptions. Such core aspects cannot be fully achieved without a transparent end-to-end human-centered traceability throughout the value chain. As a consequence, Auto-Identification (Auto-ID) technologies play a key role, since they are able to provide automated item recognition, positioning and tracking without human intervention or in cooperation with industrial operators. Although the most popular Auto-ID technologies provide a certain degree of security and productivity, there are still open challenges for future Industry 5.0 factories. This article analyzes and evaluates the Auto-ID landscape and delivers a holistic perspective and understanding of the most popular and the latest technologies, looking for solutions that cope with harsh, diverse and complex industrial scenarios. In addition, it describes a methodology for selecting Auto-ID technologies for Industry 5.0 factories. Such a methodology is applied to a specific use case of the shipbuilding industry that requires identifying the main components of a ship during its construction and repair. To validate the outcomes of the methodology, a practical evaluation of passive and active UHF RFID tags was performed in an Offshore Patrol Vessel (OPV) under construction, showing that a careful selection and evaluation of the tags enables product identification and tracking even in areas with a very high density of metallic objects. As a result, this article serves as a useful guide for industrial stakeholders, including future developers and managers that seek for deploying identification and traceability technologies in Industry 5.0 scenarios.This work was supported in part by the Auto-Identication for Intelligent Products Research Line of the Navantia-Universidade da Coruña Joint Research Unit under Grant IN853B-2018/02, and in part by the Centro de Investigación de Galicia ``CITIC,'' funded by Xunta de Galicia and the European Union (European Regional Development Fund-Galicia 2014_2020 Program) under Grant ED431G 2019/01Xunta de Galicia; IN853B-2018/02Xunta de Galicia; ED431G 2019/0
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