DEVELOPMENT OF AN AUTONOMOUS NAVIGATION SYSTEM FOR THE SHUTTLE CAR IN UNDERGROUND ROOM & PILLAR COAL MINES

In recent years, autonomous solutions in the multi-disciplinary field of the mining engineering have been an extremely popular applied research topic. The growing demand for mineral supplies combined with the steady decline in the available surface reserves has driven the mining industry to mine deeper underground deposits. These deposits are difficult to access, and the environment may be hazardous to mine personnel (e.g., increased heat, difficult ventilation conditions, etc.). Moreover, current mining methods expose the miners to numerous occupational hazards such as working in the proximity of heavy mining equipment, possible roof falls, as well as noise and dust. As a result, the mining industry, in its efforts to modernize and advance its methods and techniques, is one of the many industries that has turned to autonomous systems. Vehicle automation in such complex working environments can play a critical role in improving worker safety and mine productivity. One of the most time-consuming tasks of the mining cycle is the transportation of the extracted ore from the face to the main haulage facility or to surface processing facilities. Although conveyor belts have long been the autonomous transportation means of choice, there are still many cases where a discrete transportation system is needed to transport materials from the face to the main haulage system. The current dissertation presents the development of a navigation system for an autonomous shuttle car (ASC) in underground room and pillar coal mines. By introducing autonomous shuttle cars, the operator can be relocated from the dusty, noisy, and potentially dangerous environment of the underground mine to the safer location of a control room. This dissertation focuses on the development and testing of an autonomous navigation system for an underground room and pillar coal mine. A simplified relative localization system which determines the location of the vehicle relatively to salient features derived from on-board 2D LiDAR scans was developed for a semi-autonomous laboratory-scale shuttle car prototype. This simplified relative localization system is heavily dependent on and at the same time leverages the room and pillar geometry. Instead of keeping track of a global position of the vehicle relatively to a fixed coordinates frame, the proposed custom localization technique requires information regarding only the immediate surroundings. The followed approach enables the prototype to navigate around the pillars in real-time using a deterministic Finite-State Machine which models the behavior of the vehicle in the room and pillar mine with only a few states. Also, a user centered GUI has been developed that allows for a human user to control and monitor the autonomous vehicle by implementing the proposed navigation system. Experimental tests have been conducted in a mock mine in order to evaluate the performance of the developed system. A number of different scenarios simulating common missions that a shuttle car needs to undertake in a room and pillar mine. The results show a minimum success ratio of 70%

High latency unmanned ground vehicle teleoperation enhancement by presentation of estimated future through video transformation

Long-distance, high latency teleoperation tasks are difficult, highly stressful for teleoperators, and prone to over-corrections, which can lead to loss of control. At higher latencies, or when teleoperating at higher vehicle speed, the situation becomes progressively worse. To explore potential solutions, this research work investigates two 2D visual feedback-based assistive interfaces (sliding-only and sliding-and-zooming windows) that apply simple but effective video transformations to enhance teleoperation. A teleoperation simulator that can replicate teleoperation scenarios affected by high and adjustable latency has been developed to explore the effectiveness of the proposed assistive interfaces. Three image comparison metrics have been used to fine-tune and optimise the proposed interfaces. An operator survey was conducted to evaluate and compare performance with and without the assistance. The survey has shown that a 900ms latency increases task completion time by up to 205% for an on-road and 147 % for an off-road driving track. Further, the overcorrection-induced oscillations increase by up to 718 % with this level of latency. The survey has shown the sliding-only video transformation reduces the task completion time by up to 25.53 %, and the sliding-and-zooming transformation reduces the task completion time by up to 21.82 %. The sliding-only interface reduces the oscillation count by up to 66.28 %, and the sliding-and-zooming interface reduces it by up to 75.58 %. The qualitative feedback from the participants also shows that both types of assistive interfaces offer better visual situational awareness, comfort, and controllability, and significantly reduce the impact of latency and intermittency on the teleoperation task

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Conception d’un mécanisme intégré d’attention sélective dans une architecture comportementale pour robots autonomes

Le vieillissement de la population à travers le monde nous amène à considérer sérieusement l'intégration dans notre quotidien de robots de service afin d'alléger les besoins pour la prestation de soins. Or, il n'existe pas présentement de robots de service suffisamment avancés pour être utiles en tant que véritables assistants à des personnes en perte d'autonomie. Un des problèmes freinant le développement de tels robots en est un d'intégration logicielle. En effet, il est difficile d'intégrer les multiples capacités de perception et d'action nécessaires à interagir de manière naturelle et adéquate avec une personne en milieu réel, les limites des ressources de calculs disponibles sur une plateforme robotique étant rapidement atteintes. Même si le cerveau humain a des capacités supérieures à un ordinateur, lui aussi a des limites sur ses capacités de traitement de l'information. Pour faire face à ces limites, l'humain gère ses capacités cognitives avec l'aide de l'attention sélective. L'attention sélective lui permet par exemple d'ignorer certains stimuli pour concentrer ses ressources sur ceux utiles à sa tâche. Puisque les robots pourraient grandement bénéficier d'un tel mécanisme, l'objectif de la thèse est de développer une architecture de contrôle intégrant un mécanisme d'attention sélective afin de diminuer la charge de calcul demandée par les différents modules de traitement du robot. L'architecture de contrôle utilisé est basée sur l'approche comportementale, et porte le nom HBBA, pour Hybrid Behavior-Based Architecture. Pour répondre à cet objectif, le robot humanoïde nommé IRL-1 a été conçu pour permettre l'intégration de multiples capacités de perception et d'action sur une seule et même plateforme, afin de s'en servir comme plateforme expérimentale pouvant bénéficier de mécanismes d'attention sélective. Les capacités implémentées permettent d'interagir avec IRL-1 selon différentes modalités. IRL-1 peut être guidé physiquement en percevant les forces externes par le bias d'actionneurs élastiques utilisés dans la direction de sa plateforme omnidirectionnelle. La vision, le mouvement et l'audition ont été intégrés dans une interface de téléprésence augmentée. De plus, l'influence des délais de réaction à des sons dans l'environnement a pu être examinée. Cette implémentation a permis de valider l'usage de HBBA comme base de travail pour la prise de décision du robot, ainsi que d'explorer les limites en termes de capacités de traitement des modules sur le robot. Ensuite, un mécanisme d'attention sélective a été développé au sein de HBBA. Le mécanisme en question intègre l'activation de modules de traitement avec le filtrage perceptuel, soit la capacité de moduler la quantité de stimuli utilisés par les modules de traitement afin d'adapter le traitement aux ressources de calculs disponibles. Les résultats obtenus démontrent les bénéfices qu'apportent un tel mécanisme afin de permettre au robot d'optimiser l'usage de ses ressources de calculs afin de satisfaire ses buts. De ces travaux résulte une base sur laquelle il est maintenant possible de poursuivre l'intégration de capacités encore plus avancées et ainsi progresser efficacement vers la conception de robots domestiques pouvant nous assister dans notre quotidien

A minimally invasive surgical system for 3D ultrasound guided robotic retrieval of foreign bodies from a beating heart

The result of various medical conditions and trauma, foreign bodies in the heart pose a serious health risk as they may interfere with cardiovascular function. Particles such as thrombi, bullet fragments, and shrapnel can become trapped in a person's heart after migrating through the venous system, or by direct penetration. The severity of disruption can range from benign to fatal, with associated symptoms including anxiety, fever, cardiac tamponade, hemorrhage, infection, embolism, arrhythmia, and valve dysfunction. Injuries of this nature are common in both civilian and military populations. For symptomatic cases, conventional treatment is removal of the foreign body through open surgery via a median sternotomy, the use of cardiopulmonary bypass, and a wide incision in the heart muscle; these methods incur pronounced perioperative risks and long recovery periods. In order to improve upon the standard of care, we propose an image guided robotic system and a corresponding minimally invasive surgical approach. The system employs a dexterous robotic capture device that can maneuver inside the heart through a small incision. Visualization and guidance within the otherwise occluded internal regions are provided by 3D transesophageal echocardiography (TEE), an emerging form of intraoperative medical imaging used in interventions such as mitral valve repair and device implantation. A robotic approach, as opposed to a manual procedure using rigid instruments, is motivated by the various challenges inherent in minimally invasive surgery, which arise from attempts to perform skilled surgical tasks through small incisions without direct vision. Challenges include reduced dexterity, constrained workspace, limited visualization, and difficult hand-eye coordination, which ultimately lead to poor manipulability. A dexterous robotic end effector with real-time image guidance can help overcome these challenges and potentially improve surgical performance. However promising, such a system and approach require that several technical hurdles be resolved. The foreign body must be automatically tracked as it travels about the dynamic environment of the heart. The erratically moving particle must then be captured using a dexterous robot that moves much more slowly in comparison. Furthermore, retrieval must be performed under 3D ultrasound guidance, amidst the uncertainties presented by both the turbulent flow and by the imaging modality itself. In addressing such barriers, this thesis explores the development of a prototype system capable of retrieving a foreign body from a beating heart, culminating in a set of demonstrative in vitro experiments