5,388 research outputs found

    Human-friendly robotic manipulators: safety and performance issues in controller design

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    Recent advances in robotics have spurred its adoption into new application areas such as medical, rescue, transportation, logistics, personal care and entertainment. In the personal care domain, robots are expected to operate in human-present environments and provide non-critical assistance. Successful and flourishing deployment of such robots present different opportunities as well as challenges. Under a national research project, Bobbie, this dissertation analyzes challenges associated with these robots and proposes solutions for identified problems. The thesis begins by highlighting the important safety concern and presenting a comprehensive overview of safety issues in a typical domestic robot system. By using functional safety concept, the overall safety of the complex robotic system was analyzed through subsystem level safety issues. Safety regions in the world model of the perception subsystem, dependable understanding of the unstructured environment via fusion of sensory subsystems, lightweight and compliant design of mechanical components, passivity based control system and quantitative metrics used to assert safety are some important points discussed in the safety review. The main research focus of this work is on controller design of robotic manipulators against two conflicting requirements: motion performance and safety. Human-friendly manipulators used on domestic robots exhibit a lightweight design and demand a stable operation with a compliant behavior injected via a passivity based impedance controller. Effective motion based manipulation using such a controller requires a highly stiff behavior while important safety requirements are achieved with compliant behaviors. On the basis of this intuitive observation, this research identifies suitable metrics to identify the appropriate impedance for a given performance and safety requirement. This thesis also introduces a domestic robot design that adopts a modular design approach to minimize complexity, cost and development time. On the basis of functional modularity concept where each module has a unique functional contribution in the system, the robot “Bobbie-UT‿ is built as an interconnection of interchangeable mobile platform, torso, robotic arm and humanoid head components. Implementation of necessary functional and safety requirements, design of interfaces and development of suitable software architecture are also discussed with the design

    Situation Assessment for Mobile Robots

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    PIC4rl-gym: a ROS2 modular framework for Robots Autonomous Navigation with Deep Reinforcement Learning

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    Learning agents can optimize standard autonomous navigation improving flexibility, efficiency, and computational cost of the system by adopting a wide variety of approaches. This work introduces the \textit{PIC4rl-gym}, a fundamental modular framework to enhance navigation and learning research by mixing ROS2 and Gazebo, the standard tools of the robotics community, with Deep Reinforcement Learning (DRL). The paper describes the whole structure of the PIC4rl-gym, which fully integrates DRL agent's training and testing in several indoor and outdoor navigation scenarios and tasks. A modular approach is adopted to easily customize the simulation by selecting new platforms, sensors, or models. We demonstrate the potential of our novel gym by benchmarking the resulting policies, trained for different navigation tasks, with a complete set of metrics

    HAPTICS IN ROBOTICS AND AUTOMOTIVE SYSTEMS

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    Haptics is the science of applying touch (tactile) sensation and control to interaction with computer applications. The devices used to interact with computer applications are known as haptic interfaces. These devices sense some form of human movement, be it finger, head, hand or body movement and receive feedback from computer applications in form of felt sensations to the limbs or other parts of the human body. Examples of haptic interfaces range from force feedback joysticks/controllers in video game consoles to tele-operative surgery. This thesis deals with haptic interfaces involving hand movements. The first experiment involves using the end effector of a robotic manipulator as an interactive device to aid patients with deficits in the upper extremities in passive resistance therapy using novel path planning. The second experiment involves the application of haptic technology to the human-vehicle interface in a steer-by-wire transportation system using adaptive control

    Dynamic obstacles avoidance algorithms for unmanned ground vehicles

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    En las últimas décadas, los vehículos terrestres no tripulados (UGVs) están siendo cada vez más empleados como robots de servicios. A diferencia de los robots industriales, situados en posiciones fijas y controladas, estos han de trabajar en entornos dinámicos, compartiendo su espacio con otros vehículos y personas. Los UGVs han de ser capaces de desplazarse sin colisionar con ningún obstáculo, de tal manera que puedan asegurar tanto su integridad como la del entorno. En el estado del arte encontramos algoritmos de navegación autónoma diseñados para UGVs que son capaces de planificar rutas de forma segura con objetos estáticos y trabajando en entornos parcialmente controlados. Sin embargo, cuando estos entornos son dinámicos, se planifican rutas más peligrosas y que a menudo requieren de un mayor consumo de energía y recursos, e incluso pueden llegar a bloquear el UGV en un mínimo local. En esta tesis, la adaptación de algunos algoritmos disponibles en el estado del arte para trabajar en entornos dinámicos han sido planteados. Estos algoritmos incluyen información temporal tales como los basados en arcos de curvatura (PCVM y DCVM) y los basados en ventanas dinámicas (DW4DO y DW4DOT). Además, se ha propuesto un planificador global basado en Lattice State Planner (DLP) que puede resolver situaciones donde los evitadores de obstáculos reactivos no funcionan. Estos algoritmos han sido validados tanto en simulación como en entornos reales, utilizando distintas plataformas robóticas, entre las que se incluye un robot asistente (RoboShop) diseñado y construido en el marco de esta tesis

    Averting Robot Eyes

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    Home robots will cause privacy harms. At the same time, they can provide beneficial services—as long as consumers trust them. This Essay evaluates potential technological solutions that could help home robots keep their promises, avert their eyes, and otherwise mitigate privacy harms. Our goals are to inform regulators of robot-related privacy harms and the available technological tools for mitigating them, and to spur technologists to employ existing tools and develop new ones by articulating principles for avoiding privacy harms. We posit that home robots will raise privacy problems of three basic types: (1) data privacy problems; (2) boundary management problems; and (3) social/relational problems. Technological design can ward off, if not fully prevent, a number of these harms. We propose five principles for home robots and privacy design: data minimization, purpose specifications, use limitations, honest anthropomorphism, and dynamic feedback and participation. We review current research into privacy-sensitive robotics, evaluating what technological solutions are feasible and where the harder problems lie. We close by contemplating legal frameworks that might encourage the implementation of such design, while also recognizing the potential costs of regulation at these early stages of the technology

    An Empirical Evaluation Framework for Autonomous Vacuum Cleaners in Industrial and Commercial Settings: A Multi-Metric Approach

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    Despite advancements in cleaning automation, there is a noticeable gap in standardized evaluation methods for autonomous vacuum cleaners in industrial and commercial settings. Existing assessments often lack a unified approach, focusing narrowly on either technical capabilities or financial aspects, without integrating both perspectives. This research presents a framework for the evaluation of autonomous vacuum cleaners in industrial and commercial settings, focusing on eight key metrics. These metrics are designed to provide a unified empirical perspective of the vacuum cleaners\u27 performance, operational efficiency, cost, productivity, durability, safety, return on investment, and adaptability. The proposed framework starts with an analysis of cleaning efficiency, examining both the area covered by the cleaners and the quality of cleaning. Advanced image processing techniques are suggested for mapping the area coverage, tailored to different vacuum designs. For assessing cleaning quality, the proposal highlights the potential integration of real-time dirt detection technologies, such as gravimetric sampling and light sensors, to dynamically adapt to varying dirt concentrations and types. Operational efficiency part encompasses the assessment of battery life, charge time, and operational downtime. It advocates for a dual approach of empirical testing and analytical modeling to measure battery life and charge time accurately. The evaluation of operational downtime incorporates tracking of maintenance, charging periods, and other non-operational activities, complemented by predictive modeling for efficient future planning. The financial aspect of the proposed framework encompassed under cost metrics, considers the initial investment, operational and maintenance costs, and potential labor cost savings. This study argues that these cost analysis aids in understanding the long-term financial implications of adopting autonomous vacuum cleaners. Productivity metrics focus on the cleaning speed and the level of autonomy of the vacuum cleaners. Cleaning speed is evaluated using formulas that take into account various environmental factors, while the autonomy level is determined using Sheridan\u27s Levels of Autonomy, which reflects the vacuum\u27s operational independence and its impact on human productivity. Durability, reliability, safety, and compliance are key for vacuum cleaners, evaluated through metrics like Mean Time Between Failures, Mean Time To Repair, Service Life, safety incidents, and adherence to standards and regulations. Lastly, the suggested framework evaluates the vacuum\u27s flexibility and adaptability in different environments, such as various floor types and conditions, highlighting the importance of versatility in autonomous cleaning solutions. Article history: Received: 01/December /2022; Available online: 07/ February/2023; This work is licensed under a Creative Commons International License

    Multi-Robot Persistent Coverage in Complex Environments

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    Los recientes avances en robótica móvil y un creciente desarrollo de robots móviles asequibles han impulsado numerosas investigaciones en sistemas multi-robot. La complejidad de estos sistemas reside en el diseño de estrategias de comunicación, coordinación y controlpara llevar a cabo tareas complejas que un único robot no puede realizar. Una tarea particularmente interesante es la cobertura persistente, que pretende mantener cubierto en el tiempo un entorno con un equipo de robots moviles. Este problema tiene muchas aplicaciones como aspiración o limpieza de lugares en los que la suciedad se acumula constantemente, corte de césped o monitorización ambiental. Además, la aparición de vehículos aéreos no tripulados amplía estas aplicaciones con otras como la vigilancia o el rescate.Esta tesis se centra en el problema de cubrir persistentemente entornos progresivamente mas complejos. En primer lugar, proponemos una solución óptima para un entorno convexo con un sistema centralizado, utilizando programación dinámica en un horizonte temporalnito. Posteriormente nos centramos en soluciones distribuidas, que son más robustas, escalables y eficientes. Para solventar la falta de información global, presentamos un algoritmo de estimación distribuido con comunicaciones reducidas. Éste permite a los robots teneruna estimación precisa de la cobertura incluso cuando no intercambian información con todos los miembros del equipo. Usando esta estimación, proponemos dos soluciones diferentes basadas en objetivos de cobertura, que son los puntos del entorno en los que más se puedemejorar dicha cobertura. El primer método es un controlador del movimiento que combina un término de gradiente con un término que dirige a los robots hacia sus objetivos. Este método funciona bien en entornos convexos. Para entornos con algunos obstáculos, el segundométodo planifica trayectorias abiertas hasta los objetivos, que son óptimas en términos de cobertura. Finalmente, para entornos complejos no convexos, presentamos un algoritmo capaz de encontrar particiones equitativas para los robots. En dichas regiones, cada robotplanifica trayectorias de longitud finita a través de un grafo de caminos de tipo barrido.La parte final de la tesis se centra en entornos discretos, en los que únicamente un conjunto finito de puntos debe que ser cubierto. Proponemos una estrategia que reduce la complejidad del problema separándolo en tres subproblemas: planificación de trayectoriascerradas, cálculo de tiempos y acciones de cobertura y generación de un plan de equipo sin colisiones. Estos subproblemas más pequeños se resuelven de manera óptima. Esta solución se utiliza en último lugar para una novedosa aplicación como es el calentamiento por inducción doméstico con inductores móviles. En concreto, la adaptamos a las particularidades de una cocina de inducción y mostramos su buen funcionamiento en un prototipo real.Recent advances in mobile robotics and an increasing development of aordable autonomous mobile robots have motivated an extensive research in multi-robot systems. The complexity of these systems resides in the design of communication, coordination and control strategies to perform complex tasks that a single robot can not. A particularly interesting task is that of persistent coverage, that aims to maintain covered over time a given environment with a team of robotic agents. This problem is of interest in many applications such as vacuuming, cleaning a place where dust is continuously settling, lawn mowing or environmental monitoring. More recently, the apparition of useful unmanned aerial vehicles (UAVs) has encouraged the application of the coverage problem to surveillance and monitoring. This thesis focuses on the problem of persistently covering a continuous environment in increasingly more dicult settings. At rst, we propose a receding-horizon optimal solution for a centralized system in a convex environment using dynamic programming. Then we look for distributed solutions, which are more robust, scalable and ecient. To deal with the lack of global information, we present a communication-eective distributed estimation algorithm that allows the robots to have an accurate estimate of the coverage of the environment even when they can not exchange information with all the members of the team. Using this estimation, we propose two dierent solutions based on coverage goals, which are the points of the environment in which the coverage can be improved the most. The rst method is a motion controller, that combines a gradient term with a term that drives the robots to the goals, and which performs well in convex environments. For environments with some obstacles, the second method plans open paths to the goals that are optimal in terms of coverage. Finally, for complex, non-convex environments we propose a distributed algorithm to nd equitable partitions for the robots, i.e., with an amount of work proportional to their capabilities. To cover this region, each robot plans optimal, nite-horizon paths through a graph of sweep-like paths. The nal part of the thesis is devoted to discrete environment, in which only a nite set of points has to be covered. We propose a divide-and-conquer strategy to separate the problem to reduce its complexity into three smaller subproblem, which can be optimally solved. We rst plan closed paths through the points, then calculate the optimal coverage times and actions to periodically satisfy the coverage required by the points, and nally join together the individual plans of the robots into a collision-free team plan that minimizes simultaneous motions. This solution is eventually used for a novel application that is domestic induction heating with mobile inductors. We adapt it to the particular setting of a domestic hob and demonstrate that it performs really well in a real prototype.<br /
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