Externalising moods and psychological states in a cloud based system to enhance a pet-robot and child’s interaction

Background:This PATRICIA research project is about using pet robots to reduce pain and anxiety in hospitalized children. The study began 2 years ago and it is believed that the advances made in this project are significant. Patients, parents, nurses, psycholo- gists, and engineers have adopted the Pleo robot, a baby dinosaur robotic pet, which works in different ways to assist children during hospitalization. Methods: Focus is spent on creating a wireless communication system with the Pleo in order to help the coordinator, who conducts therapy with the child, monitor, under- stand, and control Pleo’s behavior at any moment. This article reports how this techno- logical function is being developed and tested. Results: Wireless communication between the Pleo and an Android device is achieved. The developed Android app allows the user to obtain any state of the robot without stopping its interaction with the patient. Moreover, information is sent to a cloud, so that robot moods, states and interactions can be shared among different robots. Conclusions: Pleo attachment was successful for more than 1 month, working with children in therapy, which makes the investment capable of positive therapeutic possibilities. This technical improvement in the Pleo addresses two key issues in social robotics: needing an enhanced response to maintain the attention and engagement of the child, and using the system as a platform to collect the states of the child’s progress for clinical purposes.Peer ReviewedPostprint (published version

Ground and Aerial Robots for Agricultural Production: Opportunities and Challenges

Crop and animal production techniques have changed significantly over the last century. In the early 1900s, animal power was replaced by tractor power that resulted in tremendous improvements in field productivity, which subsequently laid foundation for mechanized agriculture. While precision agriculture has enabled site-specific management of crop inputs for improved yields and quality, precision livestock farming has boosted efficiencies in animal and dairy industries. By 2020, highly automated systems are employed in crop and animal agriculture to increase input efficiency and agricultural output with reduced adverse impact on the environment. Ground and aerial robots combined with artificial intelligence (AI) techniques have potential to tackle the rising food, fiber, and fuel demands of the rapidly growing population that is slated to be around 10 billion by the year 2050. This Issue Paper presents opportunities provided by ground and aerial robots for improved crop and animal production, and the challenges that could potentially limit their progress and adoption. A summary of enabling factors that could drive the deployment and adoption of robots in agriculture is also presented along with some insights into the training needs of the workforce who will be involved in the next-generation agriculture

HERMIES-3: A step toward autonomous mobility, manipulation, and perception

HERMIES-III is an autonomous robot comprised of a seven degree-of-freedom (DOF) manipulator designed for human scale tasks, a laser range finder, a sonar array, an omni-directional wheel-driven chassis, multiple cameras, and a dual computer system containing a 16-node hypercube expandable to 128 nodes. The current experimental program involves performance of human-scale tasks (e.g., valve manipulation, use of tools), integration of a dexterous manipulator and platform motion in geometrically complex environments, and effective use of multiple cooperating robots (HERMIES-IIB and HERMIES-III). The environment in which the robots operate has been designed to include multiple valves, pipes, meters, obstacles on the floor, valves occluded from view, and multiple paths of differing navigation complexity. The ongoing research program supports the development of autonomous capability for HERMIES-IIB and III to perform complex navigation and manipulation under time constraints, while dealing with imprecise sensory information

An Integrated Testbed for Cooperative Perception with Heterogeneous Mobile and Static Sensors

Cooperation among devices with different sensing, computing and communication capabilities provides interesting possibilities in a growing number of problems and applications including domotics (domestic robotics), environmental monitoring or intelligent cities, among others. Despite the increasing interest in academic and industrial communities, experimental tools for evaluation and comparison of cooperative algorithms for such heterogeneous technologies are still very scarce. This paper presents a remote testbed with mobile robots and Wireless Sensor Networks (WSN) equipped with a set of low-cost off-the-shelf sensors, commonly used in cooperative perception research and applications, that present high degree of heterogeneity in their technology, sensed magnitudes, features, output bandwidth, interfaces and power consumption, among others. Its open and modular architecture allows tight integration and interoperability between mobile robots and WSN through a bidirectional protocol that enables full interaction. Moreover, the integration of standard tools and interfaces increases usability, allowing an easy extension to new hardware and software components and the reuse of code. Different levels of decentralization are considered, supporting from totally distributed to centralized approaches. Developed for the EU-funded Cooperating Objects Network of Excellence (CONET) and currently available at the School of Engineering of Seville (Spain), the testbed provides full remote control through the Internet. Numerous experiments have been performed, some of which are described in the paper

Internet of Robotic Things Intelligent Connectivity and Platforms

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.publishedVersio

A Bayesian network for diagnosis of networked mobile robots

International audienceThe network of communicating mobile vehicles is a subclass of Wireless Networked Control Systems (WNCS) characterized by wireless communications and mobile nodes. The integration of the wireless network into control loop, given the stochastic aspects of wireless communication and mobility of its communicating entities, can lead to problems that affect system performances. In other words, the system quality of control QoC depends on the wireless network quality of service QoS state. A diagnosis method is essential to monitor, diagnose and maintain the system in an operational state. The present paper proposes a modular multi-layer Bayesian network model for diagnosis taking into account the network failures. Results regarding the system performance are presented to illustrate the relevance of the developed Bayesian Network BN to decisions making in order to lead the system to its final goal

An eHealth-Care Driven Perspective on 5G Networks and Infrastructure

This work describes the advancements that next generation mobile networks can bring to emergency services on the basis of a fully 5G enabled medical emergency response scenario. An ambulance service combining autonomous driving, advanced on-board patient monitoring, remote diagnosis and remote control from the hospital is introduced, allowing increased levels of care during patient transport and improved early diagnosis, thus enhancing patient survival rates. Furthermore, it is shown that such an ambulance service requires a variety of different traffic types that can only be supported concurrently and with guaranteed quality of service by a high-performance network fulfilling all 5G key performance indicators. The scenario described combines a multitude of aspects and applications enabled by 5G mobile communications, including autonomous driving, ultra-high definition video streaming, tactile remote interaction and continuous sensing, into a compelling showcase for a 5G enabled future. A centralized radio access 5G network with space division multiplexed optical fronthaul using analog radio-over-fiber and optical beamforming is analyzed, fully supporting SDN and NFV for advanced network slicing and quality of service guarantee.</p

STAM: A System of Tracking and Mapping in Real Environments

We have implemented a system of tracking mobile robots and mapping an unstructured environment, using up to 25 wireless sensor nodes in an indoor setting. These sensor nodes form an ad hoc network of beacons, self-localize with respect to three anchor nodes, and then track the locations of mobile robots in the field. The system described here was motivated by search and rescue applications, and has been demonstrated in real physical environments

IoMT Supported COVID Care – Technologies and Challenges

The Internet of Things (IoT) has sparked substantial progress in the recent days of pandemic and achieved several milestones especially in healthcare. Wearable technologies have gained in popularity as a means of ensuring the health and safety of users in medical and disaster relief activities, facilitating the evolution of the Internet of Medical Things (IoMT). The IoMT is a phenomenon in which computer networks and medical equipment are linked over the Internet to allow physicians and patients to interact in real time. This coronavirus pandemic has demonstrated how unprepared our systems are for a disaster of this magnitude, as well as the necessity for robust, computationally intelligent, and profound meddling. This study piece looks at the many IoT-enabled smart solutions that could be used to respond to various aspects of this rising epidemic, from diagnosis to treatment to prevention. The paper provides a retrospective survey and identifies several obstacles and obstructions to IoT integration as an attempt to deal with coronavirus pandemic. The work concludes with a discussion of challenges and future scope to the difficulties mentioned in the bench marked works