Internet of Robotic Things: Driving Intelligent Robotics of Future - Concept, Architecture, Applications and Technologies

Batth, Ranbir Singh; Nayyar, Anand; Nagpal, Amandeep

doi:10.1109/iccs.2018.00033

Cited by 98 publications

(46 citation statements)

References 7 publications

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“…IoRT is a relatively new field, and several attempts have been made (Ray, 2016;Batth et al, 2018;Yousif, 2018) to provide an IoRT architecture. These approaches are built on the IoT reference architectures developed many years ago and focusing only on one-dimensional layered architectural view.…”

Section: Iort Architectural Approachmentioning

confidence: 99%

Internet of Robotic Things Intelligent Connectivity and Platforms

et al. 2020

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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.

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Section: Iort Architectural Approachmentioning

confidence: 99%

Internet of Robotic Things Intelligent Connectivity and Platforms

et al. 2020

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“…Observing or monitoring includes analysis of the robot system data from many data sources and types while considering the overall system state as part of maintaining situational awareness. Considering robotic monitoring capabilities, the term "Internet of Robot Things" (IoRT) [86] describes intelligent devices that can monitor events, fuse sensor data from a variety of sources, use local and distributed intelligence to determine the best course of action. A system architecture that enables monitoring [87] can integrate observational factors such as work patterns during operation (discussed previously).…”

Section: Operatementioning

confidence: 99%

Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook

Arinez

Chang

Gao

et al. 2020

Journal of Manufacturing Science and Engineering

243

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Today's manufacturing systems are becoming increasingly complex, dynamic and connected. The factory operation faces challenges of highly nonlinear and stochastic activity due to the countless uncertainties and interdependencies that exist. Recent developments in Artificial Intelligence (AI), especially Machine Learning (ML) have shown great potential to transform the manufacturing domain through advanced analytics tools for processing the vast amounts of manufacturing data generated, known as Big Data. The focus of this paper is threefold: (1) Review the State-of-the-Art applications of AI to representative manufacturing problems, (2) Provide a systematic view for analyzing data and process dependencies at multiple levels that AI must comprehend, and (3) Identify challenges and opportunities to not only further leverage AI for manufacturing, but also influence the future development of AI to better meet the needs of manufacturing. To satisfy these objectives, the paper adopts the hierarchical organization widely practiced in manufacturing plants in examining the interdependencies from the overall system level to the more detailed granular level of incoming material process streams. In doing so, the paper considers a wide range of topics from throughput and quality, supervisory control in human robotic collaboration, process monitoring, diagnosis and prognosis, finally to advances in materials engineering to achieve desired material property in process modeling and control.

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“…The most advanced concept in terms of robotics lies in IoRT, where CPSs are used to lay a strong foundation in enhancing IoT itself [ 10 ]. In IoRT systems, modern robotic technologies have been merged with cloud computing [ 31 ] and networking, integrating CPSs and IoT protocols to develop new technologies.…”

Section: Smart Technologies In Industry 40mentioning

confidence: 99%

“…Many reviews have been written in the last few years [ 8 , 9 , 10 , 11 , 12 ], yet none of them classifies the IoRT systems according to smart domains. This survey is intended to shed light on the IoRT applications associated with different smart domains in the context of Industry 4.0, defining the most recent state-of-the-art of IoRT technologies and outlining how IoRT systems could play a key role in our society.…”

Section: Introductionmentioning

confidence: 99%

Internet of Robotic Things in Smart Domains: Applications and Challenges

Romeo

Petitti

Marani

et al. 2020

Sensors

100

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With the advent of the Fourth Industrial Revolution, Internet of Things (IoT) and robotic systems are closely cooperating, reshaping their relations and managing to develop new-generation devices. Such disruptive technology corresponds to the backbone of the so-called Industry 4.0. The integration of robotic agents and IoT leads to the concept of the Internet of Robotic Things, in which innovation in digital systems is drawing new possibilities in both industrial and research fields, covering several domains such as manufacturing, agriculture, health, surveillance, and education, to name but a few. In this manuscript, the state-of-the-art of IoRT applications is outlined, aiming to mark their impact on several research fields, and focusing on the main open challenges of the integration of robotic technologies into smart spaces. IoRT technologies and applications are also discussed to underline their influence in everyday life, inducing the need for more research into remote and automated applications.

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Internet of Robotic Things: Driving Intelligent Robotics of Future - Concept, Architecture, Applications and Technologies

Cited by 98 publications

References 7 publications

Internet of Robotic Things Intelligent Connectivity and Platforms

Internet of Robotic Things Intelligent Connectivity and Platforms

Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook

Internet of Robotic Things in Smart Domains: Applications and Challenges

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