Online Searching with an Autonomous Robot

We discuss online strategies for visibility-based searching for an object hidden behind a corner, using Kurt3D, a real autonomous mobile robot. This task is closely related to a number of well-studied problems. Our robot uses a three-dimensional laser scanner in a stop, scan, plan, go fashion for building a virtual three-dimensional environment. Besides planning trajectories and avoiding obstacles, Kurt3D is capable of identifying objects like a chair. We derive a practically useful and asymptotically optimal strategy that guarantees a competitive ratio of 2, which differs remarkably from the well-studied scenario without the need of stopping for surveying the environment. Our strategy is used by Kurt3D, documented in a separate video.Comment: 16 pages, 8 figures, 12 photographs, 1 table, Latex, submitted for publicatio

System Integration of a Tour Guide Robot

In today\u27s world, people visit many attractive places. On such an occasion, It is of utmost importance to be accompanied by a tour guide, who is known to explain about the cultural and historical importance of places. Due to the advancements in technology, smartphones today have the capability to help a person navigate to any place in the world and can itself act as a tour guide by explaining a significance of a place. However, the person while looking into his phone might not watch his/her step and might collide with other moving person or objects. With a phone tour guide, the person is alone and is missing a sense of contact with other travelers. therefore a human guide is necessary to provide tours for a group of visitors. However, Human tour guides might face tiredness, distraction, and the effects of repetitive tasks while providing tour service to visitors. Robots eliminate these problems and can provide tour consistently until it drains its battery. This experiment introduces a tour-guide robot that can be used on such an occasion. Tour guide robots can navigate autonomously in a known map of a given place and at the same time interact with people. The environment is equipped with artificial landmarks. Each landmark provides information about that specific region. An Animated avatar is simulated on the screen. IBM Watson provides voice recognition and text-to-speech services for human-robot interaction

Reflectance Transformation Imaging (RTI) System for Ancient Documentary Artefacts

This tutorial summarises our uses of reflectance transformation imaging in archaeological contexts. It introduces the UK AHRC funded project reflectance Transformation Imaging for Anciant Documentary Artefacts and demonstrates imaging methodologies

Intelligent computational techniques and virtual environment for understanding cerebral visual impairment patients

Cerebral Visual Impairment (CVI) is a medical area that concerns the study of the effect of brain damages on the visual field (VF). People with CVI are not able to construct a perfect 3-Dimensional view of what they see through their eyes in their brain. Therefore, they have difficulties in their mobility and behaviours that others find hard to understand due to their visual impairment. A branch of Artificial Intelligence (AI) is the simulation of behaviour by building computational models that help to explain how people solve problems or why they behave in a certain way. This project describes a novel intelligent system that simulates the navigation problems faced by people with CVI. This will help relatives, friends, and ophthalmologists of CVI patients understand more about their difficulties in navigating their everyday environment. The navigation simulation system is implemented using the Unity3D game engine. Virtual scenes of different living environments are also created using the Unity modelling software. The vision of the avatar in the virtual environment is implemented using a camera provided by the 3D game engine. Given a visual field chart of a CVI patient with visual impairment, the system automatically creates a filter (mask) that mimics a visual defect and places it in front of the visual field of the avatar. The filters are created by extracting, classifying and converting the symbols of the defected areas in the visual field chart to numerical values and then converted to textures to mask the vision. Each numeric value represents a level of transparency and opacity according to the severity of the visual defect in that region. The filters represent the vision masks. Unity3D supports physical properties to facilitate the representation of the VF defects into a form of structures of rays. The length of each ray depends on the VF defect s numeric value. Such that, the greater values (means a greater percentage of opacity) represented by short rays in length. While the smaller values (means a greater percentage of transparency) represented by longer rays. The lengths of all rays are representing the vision map (how far the patient can see). Algorithms for navigation based on the generated rays have been developed to enable the avatar to move around in given virtual environments. The avatar depends on the generated vision map and will exhibit different behaviours to simulate the navigation problem of real patients. The avatar s behaviour of navigation differs from patient to another according to their different defects. An experiment of navigating virtual environments (scenes) using the HTC Oculus Vive Headset was conducted using different scenarios. The scenarios are designed to use different VF defects within different scenes. The experiment simulates the patient s navigation in virtual environments with static objects (rooms) and in virtual environments with moving objects. The behaviours of the experiment participants actions (avoid/bump) match the avatar s using the same scenario. This project has created a system that enables the CVI patient s parents and relatives to aid the understanding what the CVI patient encounter. Besides, it aids the specialists and educators to take into account all the difficulties that the patients experience. Then, is to design and develop appropriate educational programs that can help each individual patient

Autonomous Systems: Autonomous Systems: Indoor Drone Navigation

Drones are a promising technology for autonomous data collection and indoor sensing. In situations when human-controlled UAVs may not be practical or dependable, such as in uncharted or dangerous locations, the usage of autonomous UAVs offers flexibility, cost savings, and reduced risk. The system creates a simulated quadcopter capable of autonomously travelling in an indoor environment using the gazebo simulation tool and the ros navigation system framework known as Navigaation2. While Nav2 has successfully shown the functioning of autonomous navigation in terrestrial robots and vehicles, the same hasn't been accomplished with unmanned aerial vehicles and still has to be done. The goal is to use the slam toolbox for ROS and the Nav2 navigation system framework to construct a simulated drone that can move autonomously in an indoor (gps-less) environment

Safe navigation and human-robot interaction in assistant robotic applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Towards the simulation of cooperative perception applications by leveraging distributed sensing infrastructures

With the rapid development of Automated Vehicles (AV), the boundaries of their function alities are being pushed and new challenges are being imposed. In increasingly complex and dynamic environments, it is fundamental to rely on more powerful onboard sensors and usually AI. However, there are limitations to this approach. As AVs are increasingly being integrated in several industries, expectations regarding their cooperation ability is growing, and vehicle-centric approaches to sensing and reasoning, become hard to integrate. The proposed approach is to extend perception to the environment, i.e. outside of the vehicle, by making it smarter, via the deployment of wireless sensors and actuators. This will vastly improve the perception capabilities in dynamic and unpredictable scenarios and often in a cheaper way, relying mostly in the use of lower cost sensors and embedded devices, which rely on their scale deployment instead of centralized sensing abilities. Consequently, to support the development and deployment of such cooperation actions in a seamless way, we require the usage of co-simulation frameworks, that can encompass multiple perspectives of control and communications for the AVs, the wireless sensors and actuators and other actors in the environment. In this work, we rely on ROS2 and micro-ROS as the underlying technologies for integrating several simulation tools, to construct a framework, capable of supporting the development, test and validation of such smart, cooperative environments. This endeavor was undertaken by building upon an existing simulation framework known as AuNa. We extended its capabilities to facilitate the simulation of cooperative scenarios by incorporat ing external sensors placed within the environment rather than just relying on vehicle-based sensors. Moreover, we devised a cooperative perception approach within this framework, showcasing its substantial potential and effectiveness. This will enable the demonstration of multiple cooperation scenarios and also ease the deployment phase by relying on the same software architecture.Com o rápido desenvolvimento dos Veículos Autónomos (AV), os limites das suas funcional idades estão a ser alcançados e novos desafios estão a surgir. Em ambientes complexos e dinâmicos, é fundamental a utilização de sensores de alta capacidade e, na maioria dos casos, inteligência artificial. Mas existem limitações nesta abordagem. Como os AVs estão a ser integrados em várias indústrias, as expectativas quanto à sua capacidade de cooperação estão a aumentar, e as abordagens de perceção e raciocínio centradas no veículo, tornam-se difíceis de integrar. A abordagem proposta consiste em extender a perceção para o ambiente, isto é, fora do veículo, tornando-a inteligente, através do uso de sensores e atuadores wireless. Isto irá melhorar as capacidades de perceção em cenários dinâmicos e imprevisíveis, reduzindo o custo, pois a abordagem será baseada no uso de sensores low-cost e sistemas embebidos, que dependem da sua implementação em grande escala em vez da capacidade de perceção centralizada. Consequentemente, para apoiar o desenvolvimento e implementação destas ações em cooperação, é necessária a utilização de frameworks de co-simulação, que abranjam múltiplas perspetivas de controlo e comunicação para os AVs, sensores e atuadores wireless, e outros atores no ambiente. Neste trabalho será utilizado ROS2 e micro-ROS como as tecnologias subjacentes para a integração das ferramentas de simulação, de modo a construir uma framework capaz de apoiar o desenvolvimento, teste e validação de ambientes inteligentes e cooperativos. Esta tarefa foi realizada com base numa framework de simulação denominada AuNa. Foram expandidas as suas capacidades para facilitar a simulação de cenários cooperativos através da incorporação de sensores externos colocados no ambiente, em vez de depender apenas de sensores montados nos veículos. Além disso, concebemos uma abordagem de perceção cooperativa usando a framework, demonstrando o seu potencial e eficácia. Isto irá permitir a demonstração de múltiplos cenários de cooperação e também facilitar a fase de implementação, utilizando a mesma arquitetura de software