Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Case Study on Human-Robot Interaction of the Remote-Controlled Service Robot for Elderly and Disabled Care

The tendency of continuous aging of the population and the increasing number of people with mobility difficulties leads to increased research in the field of Assistive Service Robotics. These robots can help with daily life tasks such as reminding to take medications, serving food and drinks, controlling home appliances and even monitoring health status. When talking about assisting people in their homes, it should be noted that they will, most of the time, have to communicate with the robot themselves and be able to manage it so that they can get the most out of the robot's services. This research is focused on different methods of remote control of a mobile robot equipped with robotic manipulator. The research investigates in detail methods based on control via gestures, voice commands, and web-based graphical user interface. The capabilities of these methods for Human-Robot Interaction (HRI) have been explored in terms of usability. In this paper, we introduce a new version of the robot Robco 19, new leap motion sensor control of the robot and a new multi-channel control system. The paper presents methodology for performing the HRI experiments from human perception and summarizes the results in applications of the investigated remote control methods in real life scenarios

Developing an Autonomous Mobile Robotic Device for Monitoring and Assisting Older People

A progressive increase of the elderly population in the world has required technological solutions capable of improving the life prospects of people suffering from senile dementias such as Alzheimer's. Socially Assistive Robotics (SAR) in the research field of elderly care is a solution that can ensure, through observation and monitoring of behaviors, their safety and improve their physical and cognitive health. A social robot can autonomously and tirelessly monitor a person daily by providing assistive tasks such as remembering to take medication and suggesting activities to keep the assisted active both physically and cognitively. However, many projects in this area have not considered the preferences, needs, personality, and cognitive profiles of older people. Moreover, other projects have developed specific robotic applications making it difficult to reuse and adapt them on other hardware devices and for other different functional contexts. This thesis presents the development of a scalable, modular, multi-tenant robotic application and its testing in real-world environments. This work is part of the UPA4SAR project ``User-centered Profiling and Adaptation for Socially Assistive Robotics''. The UPA4SAR project aimed to develop a low-cost robotic application for faster deployment among the elderly population. The architecture of the proposed robotic system is modular, robust, and scalable due to the development of functionality in microservices with event-based communication. To improve robot acceptance the functionalities, enjoyed through microservices, adapt the robot's behaviors based on the preferences and personality of the assisted person. A key part of the assistance is the monitoring of activities that are recognized through deep neural network models proposed in this work. The final experimentation of the project carried out in the homes of elderly volunteers was performed with complete autonomy of the robotic system. Daily care plans customized to the person's needs and preferences were executed. These included notification tasks to remember when to take medication, tasks to check if basic nutrition activities were accomplished, entertainment and companionship tasks with games, videos, music for cognitive and physical stimulation of the patient

A Fuzzy Logic Architecture for Rehabilitation Robotic Systems

Robots are highly incorporated in rehabilitation in the last decade to compensate lost functions in disabled individuals. By controlling the rehabilitation robots from far, many benefits are achieved. These benefits include but not restricted to minimum hospital stays, decreasing cost, and increasing the level of care. The main goal of this work is to have an effective solution to take care of patients from far. Tackling the problem of the remote control of rehabilitation robots is undergoing and highly challenging. In this paper, a remote wrist rehabilitation system is presented. The developed system is a sophisticated robot ensuring the two wrist movements (Flexion /extension and abduction/adduction). Additionally, the proposed system provides a software interface enabling the physiotherapists to control the rehabilitation process remotely. The patient’s safety during the therapy is achieved through the integration of a fuzzy controller in the system control architecture. The fuzzy controller is employed to control the robot action according to the pain felt by the patient. By using fuzzy logic approach, the system can adapt effectively according to the patients’ conditions. The Queue Telemetry Transport Protocol (MQTT) is considered to overcome the latency during the human robot interaction. Based on a Kinect camera, the control technique is made gestural. The physiotherapist gestures are detected and transmitted to the software interface to be processed and be sent to the robot. The acquired measurements are recorded in a database that can be used later to monitor patient progress during the treatment protocol. The obtained experimental results show the effectiveness of the developed remote rehabilitation system

Cognitive assisted living ambient system: a survey

The demographic change towards an aging population is creating a significant impact and introducing drastic challenges to our society. We therefore need to find ways to assist older people to stay independently and prevent social isolation of these population. Information and Communication Technologies (ICT) provide various solutions to help older adults to improve their quality of life, stay healthier, and live independently for a time. Ambient Assisted Living (AAL) is a field to investigate innovative technologies to provide assistance as well as healthcare and rehabilitation to impaired seniors. The paper provides a review of research background and technologies of AAL

Design and implementation control system for a self-balancing robot based on internet of things by using Arduino microcontroller

This project is designed for attempting on developing an autonomous self-balancing robot. In this work, the two-wheel robotic system consists of a microcontroller (Arduino), Dc motor, and sensor. The Arduino is used to read the sensor data and gives the order of the motor based on the control algorithm to remaine the system is stable at different impediment. The robot is drive with Dc motor and the Arduino cannot drive. A motor driver (L298 type) is used to provide a sufficient current. The Ultrasonic sensor (used to sense impediment during the movement) and 3-axis gyroscope accelerometer sensor (To measure the robot inclination angle) to control the two-wheel robot. The controller laws allow reaching static or moving targets based on three structured IOT interactions between the elementary controllers and the sensor with actuator via Cloud environment. Regarding the technical detail must be designed based on the mathematical model. The mathematical model is used based on the model of some references, after that, the transfer function of the system is found. In this work, the MATLAB Simulink is used in the design of the controller, and the PID controller is used due to the simplicity and good activity in central systems. The PID tuner package Simulink is used to obtain the controller parameter (kp, ki, kd) that gives fast and good system response and stability. The result of the designed controller shows that the system has remained stable (remained vertically) and very fast (less than 1sec) until the system reaches the desired output

A Scoping Review on Virtual Reality-Based Industrial Training

The fourth industrial revolution has forced most companies to technologically evolve, applying new digital tools, so that their workers can have the necessary skills to face changing work environments. This article presents a scoping review of the literature on virtual reality-based training systems. The methodology consisted of four steps, which pose research questions, document search, paper selection, and data extraction. From a total of 350 peer-reviewed database articles, such as SpringerLink, IEEEXplore, MDPI, Scopus, and ACM, 44 were eventually chosen, mostly using the virtual reality haptic glasses and controls from Oculus Rift and HTC VIVE. It was concluded that, among the advantages of using this digital tool in the industry, is the commitment, speed, measurability, preservation of the integrity of the workers, customization, and cost reduction. Even though several research gaps were found, virtual reality is presented as a present and future alternative for the efficient training of human resources in the industrial field.This work was supported by Instituto Superior Tecnológico Victoria Vásconez Cuvi. The authors appreciate the opportunity to analyze topics related to this paper. The authors must also recognize the supported bringing by Universidad Tecnica de Ambato (UTA) and their Research and Development Department (DIDE) under project CONIN-P-256-2019, and SENESCYT by grants “Convocatoria Abierta 2011” and “Convocatoria Abierta 2013”

The challenges and opportunities of artificial intelligence in implementing trustworthy robotics and autonomous systems

Effective Robots and Autonomous Systems (RAS) must be trustworthy. Trust is essential in designing autonomous and semi-autonomous technologies, because “No trust, no use”. RAS should provide high quality of services, with the four key properties that make it trust, i.e. they must be (i) robust for any health issues, (ii) safe for any matters in their surrounding environments, (iii) secure for any threats from cyber spaces, and (iv) trusted for human-machine interaction. We have thoroughly analysed the challenges in implementing the trustworthy RAS in respects of the four properties, and addressed the power of AI in improving the trustworthiness of RAS. While we put our eyes on the benefits that AI brings to human, we should realise the potential risks that could be caused by AI. The new concept of human-centred AI will be the core in implementing the trustworthy RAS. This review could provide a brief reference for the research on AI for trustworthy RAS