Internet of Robotic Things in Smart Domains: Applications and Challenges

Romeo, Laura; Petitti, Antonio; Marani, Roberto; Milella, Annalisa

doi:10.3390/s20123355

Cited by 110 publications

(68 citation statements)

References 137 publications

(131 reference statements)

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“…IoRT is associated with technological convergence challenges and opportunities that call for solutions to be addressed in the future (Ray, 2016 ; Vermesan et al, 2017b ; Simoens et al, 2018 ). Various technologies are needed for ensuring the connectivity and programmability of multiple heterogeneous robotic things to implement cooperation/coordination functions, system configuration, information exchange, system dependability, and privacy.…”

Section: Internet Of Robotic Things Taxonomymentioning

confidence: 99%

“…As the concept of IoRT is evolving and expanding, there are many definitions proposed in the literature (Kara and Carlaw, 2014 ; Ray, 2016 ; Vermesan et al, 2017b ; Simoens et al, 2018 ). The definition proposed by Kara and Carlaw ( 2014 ), states that IoRT is characterized by “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,” while the definition provided by Ray ( 2016 ) focuses more on the robotic cloud concept.…”

Section: Internet Of Robotic Things Taxonomymentioning

confidence: 99%

“…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%

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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: Internet Of Robotic Things Taxonomymentioning

confidence: 99%

Section: Internet Of Robotic Things Taxonomymentioning

confidence: 99%

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Internet of Robotic Things Intelligent Connectivity and Platforms

et al. 2020

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“…A new concept of Internet of Robotic Things was defined recently, which encompasses robotics, cloud computing, and IoT. Thus, it is a challenge for the use of intelligent means like FCMs, too [52].…”

Section: Related Workmentioning

confidence: 99%

Means of IoT and Fuzzy Cognitive Maps in Reactive Navigation of Ubiquitous Robots

et al. 2021

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Development of accessible and cheap sensors as well as the possibility to transfer and process huge amounts of data offer new possibilities for many areas utilizing till now conventional approaches. Navigation of robots and autonomous vehicles is no exception in this aspect and Internet of Things (IoT), together with the means of computational intelligence, represents a new way for construction and use of robots. In this paper, the possibility to move sensors from robots to their surroundings with the help of IoT is presented and the modification of the IoT concept in the form of intelligent space as well as the concept of ubiquitous robot are shown in the paper. On an example of route tracking, we will clarify the potential of distributed networked sensors and processing their data with the use of fuzzy cognitive maps for robotic navigation. Besides, two modifications of adaptation approaches, namely particle swarm optimization and migration algorithm, are presented here. A series of simulations was performed, which are discussed and future research directions are proposed.

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“…Furthermore, using both robotics and WSNs with internet in cyber-physical systems (CPS) leads to the Internet of Robotic Things (IoRT), which has brought several changes in various domains that cover several applications in challenging environments. For example, IoRT systems can be used in manufacturing industries to execute difficult tasks such as assembling, packaging, welding, managing quality control, and so on autonomously and remotely [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Cluster-Based Data Collection by a UAV with a Limited-Capacity Battery in Robotic Wireless Sensor Networks

Gül

Erkmen

2020

Sensors

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In this work, our motivation focuses on an energy-efficient data collection problem by a mobile sink, an unmanned aerial vehicle (UAV) with limited battery capacity, in a robot network divided into several robot clusters. In each cluster, a cluster head (CH) robot allocates tasks to the remaining robots and collects data from them. Our contribution is to minimize the UAV total energy consumption coupled to minimum cost data collection from CH robots by visiting optimally a portion of the CH robots. The UAV decides the subset of CH robots to visit by considering not only the locations of all CH robots but also its battery capacity. If the UAV cannot visit all CH robots, then the CH robots not visited by the UAV transmit their data to another CH robot to forward it. The decision of transmission paths of transmitting robots is included in the cost optimization. Our contribution passes beyond the existing paradigms in the literature by considering the constant battery capacity for the UAV. We derive the optimal approach analytically for this problem. For various numbers of clusters, the performance of our strategy is compared with the approach in the close literature in terms of total energy consumed by CH robots, which affects network lifetime. Numerical results demonstrate that our strategy outperforms the approach in the close literature.

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Internet of Robotic Things in Smart Domains: Applications and Challenges

Cited by 110 publications

References 137 publications

Internet of Robotic Things Intelligent Connectivity and Platforms

Internet of Robotic Things Intelligent Connectivity and Platforms

Means of IoT and Fuzzy Cognitive Maps in Reactive Navigation of Ubiquitous Robots

Energy-Efficient Cluster-Based Data Collection by a UAV with a Limited-Capacity Battery in Robotic Wireless Sensor Networks

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