RFID Localisation For Internet Of Things Smart Homes: A Survey

The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Localisation in indoor positioning systems plays an important role in the IoT. Location Based IoT applications range from tracking objects and people in real-time, assets management, agriculture, assisted monitoring technologies for healthcare, and smart homes, to name a few. Radio Frequency based systems for indoor positioning such as Radio Frequency Identification (RFID) is a key enabler technology for the IoT due to its costeffective, high readability rates, automatic identification and, importantly, its energy efficiency characteristic. This paper reviews the state-of-the-art RFID technologies in IoT Smart Homes applications. It presents several comparable studies of RFID based projects in smart homes and discusses the applications, techniques, algorithms, and challenges of adopting RFID technologies in IoT smart home systems.Comment: 18 pages, 2 figures, 3 table

Whisking with robots from rat vibrissae to biomimetic technology for active touch

This article summarizes some of the key features of the rat vibrissal system, including the actively controlled sweeping movements of the vibrissae known as whisking, and reviews the past and ongoing research aimed at replicating some of this functionality in biomimetic robots

Augmented reality (AR) for surgical robotic and autonomous systems: State of the art, challenges, and solutions

Despite the substantial progress achieved in the development and integration of augmented reality (AR) in surgical robotic and autonomous systems (RAS), the center of focus in most devices remains on improving end-effector dexterity and precision, as well as improved access to minimally invasive surgeries. This paper aims to provide a systematic review of different types of state-of-the-art surgical robotic platforms while identifying areas for technological improvement. We associate specific control features, such as haptic feedback, sensory stimuli, and human-robot collaboration, with AR technology to perform complex surgical interventions for increased user perception of the augmented world. Current researchers in the field have, for long, faced innumerable issues with low accuracy in tool placement around complex trajectories, pose estimation, and difficulty in depth perception during two-dimensional medical imaging. A number of robots described in this review, such as Novarad and SpineAssist, are analyzed in terms of their hardware features, computer vision systems (such as deep learning algorithms), and the clinical relevance of the literature. We attempt to outline the shortcomings in current optimization algorithms for surgical robots (such as YOLO and LTSM) whilst providing mitigating solutions to internal tool-to-organ collision detection and image reconstruction. The accuracy of results in robot end-effector collisions and reduced occlusion remain promising within the scope of our research, validating the propositions made for the surgical clearance of ever-expanding AR technology in the future

Implementation of safe human robot collaboration for ultrasound guided radiation therapy

This thesis shows that safe human-robot-interaction and Human Robot Collaboration is possible for Ultrasound (US) guided radiotherapy. Via the chosen methodology, all components (US, optical room monitoring and robot) could be linked and integrated and realized in a realistic clinical workflow. US guided radiotherapy offers a complement and alternative to existing image-guided therapy approaches. The real-time capability of US and high soft tissue contrast allow target structures to be tracked and radiation delivery to be modulated. However, Ultrasound guided radiation therapy (USgRT) is not yet clinically established but is still under development, as reliable and safe methods of image acquisition are not yet available. In particular, the loss of contact of the US probe to the patient surface poses a problem for patient movements such as breathing. For this purpose, a Breathing and motion compensation (BaMC) was developed in this work, which together with the safe control of a lightweight robot represents a new development for USgRT. The developed BaMC can be used to control the US probe with contact to the patient. The conducted experiments have confirmed that a steady contact with the patient surface and thus a continuous image acquisition can be ensured by the developed methodology. In addition, the image position in space can be accurately maintained in the submillimeter range. The BaMC seamlessly integrates into a developed clinical workflow. The graphical user interfaces developed for this purpose, as well as direct haptic control with the robot, provide an easy interaction option for the clinical user. The developed autonomous positioning of the transducer represents a good example of the feasibility of the approach. With the help of the user interface, an acoustic plane can be defined and autonomously approached via the robot in a time-efficient and precise manner. The tests carried out show that this methodology is suitable for a wide range of transducer positions. Safety in a human-robot interaction task is essential and requires individually customized concepts. In this work, adequate monitoring mechanisms could be found to ensure both patient and staff safety. In collision tests it could be shown that the implemented detection measures work and that the robot moves into a safe parking position. The forces acting on the patient could thus be pushed well below the limits required by the standard. This work has demonstrated the first important steps towards safe robot-assisted ultrasound imaging, which is not only applicable to USgRT. The developed interfaces provide the basis for further investigations in this field, especially in the area of image recognition, for example to determine the position of the target structure. With the proof of safety of the developed system, first study in human can now follow