Data Exchange Techniques for Internet of Robotic Things: Recent Developments

The world we live in is where a human-machine connection is a barometer, and this tendency is only growing to provide richer and universal human reminiscences. New technologies, as well as the fusion of different classes of current technologies, are used to create such unique solutions. The Internet of Robotic Things (IoRT) is the product of collaboration between robotics and the Internet of Things (IoT), which has opened up incredible potential for localized self-sufficient solutions. Robots can collect accurate data from the environment and provide a comprehensive service instantaneously. Being an amalgamation of two different concepts i.e. IoT and Robotics, the IoRT system is anticipated to benefit both by expanding their potential to innovative heights. This paper gives a concise introduction to the communication architecture of the IoRT system. The taxonomy of various data exchange protocols used in an IoRT system is proposed. The necessary improvements in protocols that are required to enhance communication in an IoRT system are presented. A Review of some data exchange methodologies based on Artificial Intelligence (AI) for secure and reliable communication is also given in this paper. The key motive of this paper is to understand the data exchange within an IoRT system using common communication protocols.

IoRT system so that it can be made possible to enhance the 146 quality of data exchange between IoRT systems. By under-147 standing and studying different data exchange techniques, 148 the new researchers can improve the IoRT communication 149 systems and can also reduce or minimize the various existing 150 limitations. 151 Therefore, the study finds this issue very important and so, 152 this paper gives an insight into different data exchange sys-153 tems available for IoRT with their characteristics, advantages, 154 disadvantages, and future difficulties. The Internet of Things focuses on enabling services for 158 omnipresent monitoring, sensing, and tracking whereas robot 159 communities are more concerned with bringing forth action, 160 interaction, and self-governing behaviour. Collaborating the 161 two and establishing an IoRT system would offer momentous 162 value. The Internet of Robotic Things aims to increase Inter-163 net usage by allowing robots to access external resources over 164 the Internet. IoRT systems are made up of several Internet-165 connected components such as robots, sensors, and clouds. 166 Each component is linked together through communication 167 protocols, forming a system of systems. 168 Depending on the mechanisms and technologies, there 169 exists a variety of Robots. Generally, these Robots must 170 possess the following three capabilities (i-iii): These capabilities called the ''sense-think-act'' formula 175 enable Robots to accomplish a variety of jobs without 176 any extrinsic stimuli, therefore, providing them autonomy. 177 The abilities of Robots and their description are given in 178 Table 2. IoRT is separated into five primary layers, as per the 179 research of Ray [6], which is one of the layers accountable 180 for creating Internet connections. He described many IoT 181 protocols that facilitate it, a few of which use a messag-182 ing or notifying architecture having a broker to exchange 183 messages. 184 The messaging protocol which has the broker elimi-185 nates the data exchange restriction placed by firewalls and 186 Network Address Translation (NAT) mechanisms, allowing 187 bi-directional information exchange between end devices on 188 the Internet, making it a critical technology for achieving the 189 IoT's first proposition, ''Connecting all things.'' A robotic 190 device may be viewed as an influential processing and actu-191 ation machine that can also navigate here and there, from the 192 IoT viewpoint. IoT may be viewed as a tool for robots to 193 improve their sensing capability and enhance their steering, 194 manoeuvring, and maintenance operations [9], [14]. 195 As a result, Robots join forces with objects and smartly 196 collaborate toward a communal purpose, in an IoRT system. 197 This became feasible with the advent of a variety of effec-198 tive wireless data exchange technology that can connect the 199 Internet of Things and Robots.
IPv6 protocol, which has been adjusted to suit low-power IoRT's communication architecture [18].
getting incredibly capable of making appropriate judgements 246 in the educational realm, or they might be self-subsistent and 247 receive a small number of directives from a remote command 248 center. They can be mobile robots with wheels or stationary 249 nodes, as in industrial robotics. They have different functions 250 and come in many sizes, including fixed arms, tiny bots, 251 mobile ground robots, and even aerial robots.

252
Robots and objects might roam about while still being con-253 nected as a network, thanks to wireless communication tech-254 nologies that are enhancing device mobility. Robotic and IoT 255 devices might be connected to separate wireless networks. 256 The communication layer would then be required to provide 257 data exchange protocols. Figure 4 316 Jia et al. [22], in their research, presented an Internet-317 based robotic system that implements networking connec-318 tions between a distant robotic system and a client using 319 the Common Object Request Broker Architecture(CORBA). 320 To deal with communication delays, the author created the 321 robot control server, that permits the handler or user to handle 322 the telerobotic system on a task-by-task basis. The subsist 323 image feedback server, which delivers live picture responses 324 to a distant user, has also been built. 325 Vermesan et al. [23], discuss the intelligent connectivity of 326 IoRT applications. According to the author, mobile cellular 327 and upgraded wireless technologies will enable communi-328 cation across vertical domains of IoRT. As cellular con-329 nection and 5G are introduced to unlicensed spectrum, the 330 new 5G NR in unlicensed spectrum (NR-U) is vital for 331 upcoming IoRT approaches. NR-U can increase coverage 332 capacity, accessibility, dependability, and precise timing by 333 supporting both license-assisted and autonomous utilization 334 of unlicensed spectrum. 335 Razafimandimby et al. [13], [24], used an ANN algorithm 336 and scheme based on IoT to address the crucial technology for 337 maintaining the global interconnection between devices in an 338 IoRT system and providing the required Quality of Service 339 (QoS). In [13], the author represented Multi-Robot systems 340 by a graph G(E, V ), where, E represents the edge set and V 341 is a vertex set representing an IoRT robot. Here, E is defined 342 in (1).  (2).    The algorithms suggested by the author enable the entire

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IoRT robot network to drift to the specified distance and 372 therefore to the befitting data exchange quality.     (iii) Networks and chipsets at a minimal cost.

458
(iv) Data transmission throughput power is limited.
where, 496 X is the distance between two antennas. The formula of 497 coverage range can be given in (6).  smart sensor s is given as in (7). The formula for computing the efficiency of data coding is 540 given in (11) as follows: To conclude the lifetime of a sensor network and to compute 544 the cost of transmitted energy of a sensor node, the energy 545 index I e is used [43]. The I e is given in (12).
where, 548 L p is the length of the packet. It is used to define the octets transmitted per second on a 556 particular link in relevance with real-time throughput [43]. 557 The analytical formula for real-time throughput T p is given 558 as follows in (13).
where, 561 n is the total data transmitted.

562
T f is the time taken to transmit a data frame.

563
T b is the backoff time needed.

566
Artificial intelligence is difficult to characterize accurately. 567 The founder of AI, John McCarthy, described AI as ''the engi-568 neering and science of constructing intelligent machines.'' 569 As a result, AI alludes to the capacity of robots to respond 570 to data and information and create results in an approach 571 comparable to how people learn, make decisions, and solve 572 problems. Furthermore, AI is always improving, allowing 573 robots to get smarter and smarter. Machine intellect means 574 Teleoperation or independent communication is also 608 possible [6]. Robots that are entirely controlled by human 609 operators via communication networks are referred to as 610 teleoperated robots. Autonomous robots, on the other hand, 611 are capable of doing tasks or acting alone. In [46], the 612 authors have discussed effective communication in cooper-613 ating robot teamwork. Information sharing between robots 614 must also provide collision avoidance and preserve the 615 communication link's quality. Energy and power metrics, 616 quality-of-service (QoS) metrics, dependability, movability, 617 collision avoidance, connection, and robot cooperation are 618 the most often utilized metrics for robot communication sys-619 tems. A great deal of study has been done on robot-team 620 communication [47], [48].

621
When the robots engaged are on the ground, in the sky, 622 in water, or other surroundings, as depicted in Figure 7, intel-623 ligent robotic communication is necessary. AI improves the 624 robot's capabilities as well. For several years, AI approaches 625 have improved robot abilities in areas such as sensor data 626 fusion, processing information, contextual identification, and 627 decision-making. DL and ML algorithms are enhancing the 628 potential of robotic systems. The evolution of AI algorithms 629 promotes (a-c): The intellectual ability of autonomous robots is focused on 635 intelligent machines that have a wide range of operating 636 skills and high redundancy while completing tasks in groups. 637 The system's scalability, adaptability, and fault tolerance 638 must all be guaranteed. [55], [56], [57], [58], [59], [60], [61], [62]. These studies are 662 fascinating, but they only apply to a few aspects of robot and low interference levels during network transmission. 697 As a result, the RL allowed every UAV to choose its data 698 exchange power, next position, and cell association. The data 699 demonstrate that higher wifi delay per UAV and higher UAV 700 elevation both help to reduce interference levels.

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The authors, on the other hand, neglected to account 702 for latency and drone interference. The research [56], [62] 703 focuses on using machine learning to optimize UAV sites and 704 forecast user actions. Additionally, robotic data communi-705 cation entails not only determining signal intensity between 706 robots, but also establishing some criteria to examine, such as 707 context, kind of information, and where the signal originates. 708 As a result, robot data exchange must be fully realized. The 709 authors of [61] concentrated on the Recurrent Neural Net-710 work (RNN) approach for useful and proficient end-to-end 711 widespread interaction to enable robots to interact with one 712 another and achieve the aim. The suggested works were sep-713 arated into three elements to accomplish this: negotiations, 714 defuzzification, and end-to-end data exchange. RNN assists 715 robots in making appreciative decisions based on received 716 signals and after discussion to prevent robot disputes.

717
Additionally, it enables receiving robots to progressively 718 receive signals from dispatcher robots and then shift to the 719 correspondent position following the RNN output. As a 720 result, the receiver robot may reach a specific destination 721 from anywhere. In [13], the authors have addressed the issue 722 of combining AI, IoT, and robotics, and came up with the 723 notion of the IoRT. The research focuses on robot aggregate 724 exposure and connection preservation. The neural network 725 approach was utilized to make a middle course between the 726 robots' connection and the required QoS. The results revealed 727 that the ANN approach had benefits in terms of connectivity, 728 energy usage, and convergence time. The authors, on the 729 other hand, have not offered a determinable account of the 730 AI diversity that existed. 731 Arsénio et al. [54] emphasized the internet of intelligent 732 things (IoIT), which integrated AI into networking technolo-733 gies and objects. For achieving the operational needs and ''the 734 cost efficiency of the vehicle networks''.

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AI methods like machine learning (ML) are employed 736 as proficient tools to handle challenges encountered in 5G 737 wireless data exchanges [63] (e.g., caching, processing, and 738 data exchange processes). To allow new connections, cellular 739 and wireless communication networks must provide con-740 ventional/assured latency, which has become the facilitator 741 for the next coming generation of IoRT intelligent services. 742 Broadcast systems and/or peer-to-peer can be used by IoRT 743 devices for information exchange and direct communication. 744 Khan et al. [64] propose an AI-based algorithm named 745 Artificial Bee Colony (ABC) so that devices within an IIoT 746 system can act intelligently and safeguard the confidentiality 747 and authenticity of data and devices. They proposed this 748 algorithm for secure communication and better network con-749 nectivity of an IIoT ecosystem. 750 Xia et al. [65] scrutinized the power control strategy of 751 secure intelligent data exchange with Statistic Channel State 752 VOLUME 10,2022 Another important aspect of the IoRT paradigm is mobility 807 management. Because of the hard processing and power lim-808 its, conventional mobility-supporting protocols for Vehicular 809 Ad Hoc Networks (VANETs), sensor networks, Mobile Ad 810 Hoc Networks (MANETs) and are unable to effectively cope 811 with common IoRT devices. To keep track of the device's 812 location and response to topological changes, movement 813 tracking is required. 814 Furthermore, the energy needs of IoRT are yet unmet. 815 A few routing protocols, as previously mentioned, offer low-816 power data exchange, however, they are still in the early 817 stages of development. As a result, green technologies must 818 be used to make IoRT devices as power-efficient as feasible. 819

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In the context of data exchange in robotic systems, the pur-821 pose of cyber security is to minimize the impact of vulnerabil-822 ities and protect robotic systems from cyber attacks. This task 823 is often challenging and necessitates the introduction of some 824 specific requirements. These requirements are commonly 825 named as CIA-Triad, referring to the following three (i-iii) 826 pillars of cyber-security, Although these three principles are the keystone of the secu-831 rity infrastructure of any organization, there are some addi-832 tional requirements such as accuracy and safety, that a robotic 833 system needs to meet. Figure 8 shows the security scenario of 834 a robotic system.

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All these sources of attacks generate a great deal of threat to 886 the robotic system and its data exchange methodologies.

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To secure Robotic communication and robotic systems it is 890 very important to maintain and implement effective security 891 measures. There is a need for a strong multi-authentication 892 procedure, along with the verification and identification pro-893 cess. Securing robotic systems, and their communication is 894 not an easy task, however, it is neither impossible. Hence, 895 a variety of cryptographic, non-cryptographic, and AI-based 896 solutions are available there to countermeasure the various 897 cyber security attacks.

900
Before proceeding to know about the various enhancements 901 made to some wireless communication protocols, it is neces-902 sary to understand why these enhancements are done. Why 903 there is a need to improve the existing wireless protocols? 904 This question is very important and has relevance because it 905 serves as the base of these very improvements done to wire-906 less communication protocols. This question can be simply 907 answered by saying that ''IoT systems that are supported by 908 these protocols +v are slightly different from IoRT systems 909 with Robots as end devices.'' physical world. Depending upon these instructions 927 they operate and drive the system.

928
(ii) On the working ground, or via the network (multi- 929 robot system), robots can exchange data with one 930 another in real-time.

931
Now, as per i, the distinction between IoT and IoRT is the 932 position of sensors and actuators, whether they are at the 933 center of the system or on the edge. In IoT, the sensors are 934 located centrally but the actuators in some situations can 935 directly affect the objects in physical space.

936
In contrast, IoRT systems have Robots at the center, which 937 includes drive systems. There is communication between 938 Robots and physical entities, which is essential, so the physi-939 cal security and safety of Robots must be ensured. Sensors 940 are used by both robots and IoT devices to perceive their 941 surroundings, analyze data fast, and decide how to react. Most 942 IoT solutions can only perform well-defined tasks, whereas 943 robots can anticipate circumstances. The primary distinc-944 tion between the IoT and the robotics society is that robots 945 perform real-world tasks and are physically present. They 946 take action. The focus of IoT has shifted from cyberspace 947 to the physical side, and this is where the efforts are coming 948 together [71].

949
Therefore, it becomes significant to make sure the upright-950 ness of extrinsic commands is given to the Robots. If there 951 will be any inconsistency or deficiency in the instruction 952 given to the Robots, it will make them go out of control.

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So, if the Robots in an IoRT system need to act in control 954 properly after receiving instruction from an external source or 955 remote location, the consistency, and integrity of the system 956 must be enhanced. The driving force behind the enhanced 957 system is the improvements that are done to some of the 958 wireless communication protocols.

959
These improvements will enhance the entire communica-960 tion system within an IoRT system and will uplift the quality 961 of Data Exchange between different Robots, humans, and 962 Robots, and also between the Robots and other devices. The IEEE 802.15.4 standard, which is built on radio trans-965 missions, allows small devices that run on batteries or solar 966 power to connect wirelessly across short distances.

967
To maintain operations at low power and moderate access 968 control mechanisms were developed so that the radio may 969 be kept off the majority of the occasion. It offers modest 970 data rates, although they are suitable for these sensor devices 971 with payloads that are projected to be below. To guarantee 972 excellent dependability and energy savings at the same time 973 as minimizing end-to-end latency latest wireless standards 974 have been created.  The IEEE 802.11 wireless protocol, sometimes known as 1038 WiFi, is used to link devices within a wireless local area 1039 network. Multiple devices are interconnected across a small 1040 distance of a few 10's meters to 100 meters, but the range may 1041 be broadened by forming a mesh. The movability assistance 1042 and wide exposure limits provided by WiFi networks would 1043 help an IoRT system.

1044
The IEEE 802.11ah is as follows (i-iv): 1045 (i) Less power is used and has a range of almost a 1046 kilometer.

1047
(ii) Because it operates in the megahertz spectrum, it has 1048 high incursion around obstructions.

1049
(iii) For low-power operations, it has pre-programmed 1050 sleep and waking cycles.

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(iv) Supports a communication range that is twice as far 1052 as standard WiFi.

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The IEEE 802.11ax is pointed out below (i-ii):

1054
(i) To increase power efficiency, various groupings of 1055 devices are given varying waking-up times.

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(ii) The end-to-end data transmission latency may be 1057 kept consistent and stable across all nodes.

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In this paper, we have given an insight into various method-1060 ologies used for data exchange in IoRT systems. We have 1061 mainly focused on wireless connectivity technologies, their 1062 comparison, and their improvements. Some AI techniques 1063 used for robotic data exchange are also presented. We have 1064 presented a brief introduction to cyber security in robotic 1065 systems, the levels of attacks, and their sources. The data 1066 communication problems in IoRT systems are also listed.

1067
The problems that presently exist in the IoRT data 1068 exchange techniques are not impossible to solve. These prob-1069 lems can be solved by the great effort of researchers by using 1070 new fast, reliable, and evolving techniques and by modifying 1071 the existing network technologies, some of which are men-1072 tioned above in Section VIII. We can perform a comparative 1073 analysis of available data exchange techniques and choose the 1074 most efficient one. Also, we can design a new IoRT system 1075 based on the existing ones. For example, for security issues, 1076 we can use blockchain technology or some lightweight cryp-1077 tographic algorithms. For quality message service, AMQP 1078 over RT-Middleware can be used. For intelligent communi-1079 cation, various AI techniques like ANN, PSO, Fussy logic, 1080 Ml, and DL can be used as mentioned in Section V.

1081
In the future, we intend to work on solving the problems 1082 that presently exist for data exchange in IoRT. We will work 1083 on cyber security for IoRT in depth in the future and intend to 1084 develop a threat model for it. Also, we will discuss in detail 1085 VOLUME 10, 2022 p. 104, Sep. 2020, doi: 10.3389/frobt.2020.00104.

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[24] C. Razafimandimby  Researcher at the Hydrogen, and Fuel Cell Depart-1442 ment, National Research and Development Insti-1443 tute for Cryogenics and Isotopic Technologies 1444 (ICSI Rm. Valcea). Her Ph.D. topic is ''theoret-1445 ical and practical contribution regarding sustain-1446 ing with hybrid energy a passive house'' with the 1447 Faculty of Building Services Engineering, Tech-1448 nical University of Cluj-Napoca, Romania. She 1449 is also responsible at ICSI for the project ''smart 1450 conductive charging station, fixed and mobile, for electric propulsion trans-1451 portation (SMiLE-EV).'' Her scientific activity materialized in 12 book 1452 chapters published abroad, and more than 50 scientific papers published 1453 in international/national conference proceedings and journals indexed in 1454 WoS/other international databases. Also, she is a Team Member in another 1455 research contract with Suceava University and has one patent application.