Computational Foundations for Safe and Efficient Human-Robot Collaboration in Assembly Cells

Human and robots have complementary strengths in performing assembly operations. Humans are very good at perception tasks in unstructured environments. They are able to recognize and locate a part from a box of miscellaneous parts. They are also very good at complex manipulation in tight spaces. The sensory characteristics of the humans, motor abilities, knowledge and skills give the humans the ability to react to unexpected situations and resolve problems quickly. In contrast, robots are very good at pick and place operations and highly repeatable in placement tasks. Robots can perform tasks at high speeds and still maintain precision in their operations. Robots can also operate for long periods of times. Robots are also very good at applying high forces and torques. Typically, robots are used in mass production. Small batch and custom production operations predominantly use manual labor. The high labor cost is making it difficult for small and medium manufacturers to remain cost competitive in high wage markets. These manufactures are mainly involved in small batch and custom production. They need to find a way to reduce the labor cost in assembly operations. Purely robotic cells will not be able to provide them the necessary flexibility. Creating hybrid cells where humans and robots can collaborate in close physical proximities is a potential solution. The underlying idea behind such cells is to decompose assembly operations into tasks such that humans and robots can collaborate by performing sub-tasks that are suitable for them. Realizing hybrid cells that enable effective human and robot collaboration is challenging. This dissertation addresses the following three computational issues involved in developing and utilizing hybrid assembly cells: - We should be able to automatically generate plans to operate hybrid assembly cells to ensure efficient cell operation. This requires generating feasible assembly sequences and instructions for robots and human operators, respectively. Automated planning poses the following two challenges. First, generating operation plans for complex assemblies is challenging. The complexity can come due to the combinatorial explosion caused by the size of the assembly or the complex paths needed to perform the assembly. Second, generating feasible plans requires accounting for robot and human motion constraints. The first objective of the dissertation is to develop the underlying computational foundations for automatically generating plans for the operation of hybrid cells. It addresses both assembly complexity and motion constraints issues. - The collaboration between humans and robots in the assembly cell will only be practical if human safety can be ensured during the assembly tasks that require collaboration between humans and robots. The second objective of the dissertation is to evaluate different options for real-time monitoring of the state of human operator with respect to the robot and develop strategies for taking appropriate measures to ensure human safety when the planned move by the robot may compromise the safety of the human operator. In order to be competitive in the market, the developed solution will have to include considerations about cost without significantly compromising quality. - In the envisioned hybrid cell, we will be relying on human operators to bring the part into the cell. If the human operator makes an error in selecting the part or fails to place it correctly, the robot will be unable to correctly perform the task assigned to it. If the error goes undetected, it can lead to a defective product and inefficiencies in the cell operation. The reason for human error can be either confusion due to poor quality instructions or human operator not paying adequate attention to the instructions. In order to ensure smooth and error-free operation of the cell, we will need to monitor the state of the assembly operations in the cell. The third objective of the dissertation is to identify and track parts in the cell and automatically generate instructions for taking corrective actions if a human operator deviates from the selected plan. Potential corrective actions may involve re-planning if it is possible to continue assembly from the current state. Corrective actions may also involve issuing warning and generating instructions to undo the current task.

Idiotypic Immune Networks in Mobile Robot Control

Jerne's idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens. The theory has proved the most popular Artificial Immune System (AIS) model for incorporation into behavior-based robotics but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with non-idiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a Reinforcement Learning based control system (RL) is described and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.

Teleoperación de un robot móvil mediante dispositivos Android

Resumen: En el siguiente trabajo se aborda un problema para solventar la comunicación con los robots del departamento MAPIR de la Universidad de Málaga, anteriormente sólo podían ser teleoperados mediante comandos escritos en Skype, así que se procede a diseñar un cliente móvil para Android que nos permite conectarse en tiempo real a un robot, obtener la imagen de lo que su cámara capta y además permitir su teleoperación. Por su parte, el robot corre un servidor que administra esos datos al cliente para trabajar conjuntamente. Dicho trabajo se desarrolla haciendo uso de nuevas tecnologias y protocolos como es WebRTC (de Google) para el intercambio de imágenes y del lado del servidor, se ha usado NodeJS.

Integración de Arbotix, Raspberry Pi y motores Dynamixel Ax-12+ para un robot humanoide que busca y patea pelotas

En este artículo se presenta a DeBuPa (Detección Búsqueda Pateo) un humanoide de tamaño pequeño (38 cm de alto) construido con las piezas del kit Bioloid. Del kit se ha excluido la tarjeta CM-510 para sustituirla por la tarjeta controladora Arbotix, que será la que controle los 16 motores Dynamixel Ax-12+ (para mover al robot) y 2 servomotores analógicos (para mover la cámara). Además se ha agregado un mini computador Raspberry Pi, con su cámara, para que el robot pueda detectar y seguir la pelota de forma autónoma. Todos estos componentes deben ser coordinados para que se logre cumplir la tarea de detectar, seguir y patear la pelota. Por ello se hace necesaria la comunicación entre la Arbotix y la Raspberry Pi. La herramienta empleada para ello es el framework ROS (Robot Operating System). En la Raspberry Pi se usa el lenguaje C++ y se ejecuta un solo programa encargado de captar la imagen de la cámara, filtrar y procesar para encontrar la pelota, tomar la decisión de la acción a ejecutar y hacer la petición a la Arbotix para que dé la orden a los motores de ejecutar el movimiento. Para captar la imagen de la cámara se ha utilizado la librería RasPiCam CV. Para filtrar y procesar la imagen se ha usado las librerías de OpenCV. La Arbotix, además de controlar los motores, se encarga de monitorizar que el robot se encuentre balanceado, para ello usa el sensor Gyro de Robotis. Si detecta un desbalance de un cierto tamaño puede saber si se ha caído y levantarse.

Mejoras en el control y sistema de comunicaciones del robot Ballbot-ULL

Este proyecto de fin de carrera forma parte de un proyecto más extenso. Supone la construcción de un robot móvil y autónomo capaz de recibir información del entorno que le rodea y ser capaz de recoger pelotas inmóviles de una pista de tenis.

Epidemiology of injuries in female high school soccer players.

Background: Sport is a compulsory activity in schools in South Africa. Female learners participating in soccer are more vulnerable to injuries than males. Objective: This study determined the epidemiology of injuries in female high school soccer players. Methods: A cross sectional survey captured the epidemiology of injuries in the players. The population included 200 players from 27 high schools in one district between the ages of 14 to 19 years. A self-administered questionnaire was used to collect data. Results: Only 85 scholars from 8 schools participated. From the 85 respondents, 31 (36.5%) sustained injuries. Only 61 injuries were reported by the injured players. The injury prevalence for the season was 36.5%. The rate of injury was 90 per 1000 athlete exposure hours during the season. The defenders and midfielders sustained the most injuries. Most injuries reported were contact in nature. More injuries occurred during training than during matches. The lower extremity (77.8%) was injured more than the upper extremity (22.2%). The knee (22.2%) and ankle (15.9%) were the most frequently injured body parts. Muscle injury was the most commonly reported followed by bruising. Conclusion: Prevalence of injuries was high with the lower limb, specifically the knee and ankle being commonly injured.

Diseño e Implementación de un robot de conocimiento para la extracción de información de los Social Media y Web

Las transformaciones tecnológicas y de información que está experimentando la sociedad, especialmente en la última década, está produciendo un crecimiento exponencial de los datos en todos los ámbitos de la sociedad. Los datos que se generan en los diferentes ámbitos se corresponden con elementos primarios de información que por sí solos son irrelevantes como apoyo a las tomas de decisiones. Para que estos datos puedan ser de utilidad en cualquier proceso de decisión, es preciso que se conviertan en información, es decir, en un conjunto de datos procesados con un significado, para ayudar a crear conocimiento. Estos procesos de transformación de datos en información se componen de diferentes fases como la localización de las fuentes de información, captura, análisis y medición.Este cambio tecnológico y a su vez de la sociedad ha provocado un aumento de las fuentes de información, de manera que cualquier persona, empresas u organización, puede generar información que puede ser relevante para el negocio de las empresas o gobiernos. Localizar estas fuentes, identificar información relevante en la fuente y almacenar la información que generan, la cual puede tener diferentes formatos, es el primer paso de todo el proceso anteriormente descrito, el cual tiene que ser ejecutado de manera correcta ya que el resto de fases dependen de las fuentes y datos recolectados. Para la identificación de información relevante en las fuentes se han creado lo que se denomina, robot de búsqueda, los cuales examinan de manera automática una fuente de información, localizando y recolectando datos que puedan ser de interés.En este trabajo se diseña e implementa un robot de conocimiento junto con los sistemas de captura de información online para fuentes hipertextuales y redes sociales.

ROBOT CEMAR: identificación de las capacidades emprendedoras de sus creadores

El XXI Congreso Latinoamericano sobre Espíritu Empresarial, se realizó en la Universidad Icesi los días 6, 7 y 8 de abril de 2011.

Genetic algorithm seeding of idiotypic networks for mobile-robot navigation

Robot-control designers have begun to exploit the properties of the human immune system in order to produce dynamic systems that can adapt to complex, varying, real-world tasks. Jerne’s idiotypic-network theory has proved the most popular artificial-immune-system (AIS) method for incorporation into behaviour-based robotics, since idiotypic selection produces highly adaptive responses. However, previous efforts have mostly focused on evolving the network connections and have often worked with a single, preengineered set of behaviours, limiting variability. This paper describes a method for encoding behaviours as a variable set of attributes, and shows that when the encoding is used with a genetic algorithm (GA), multiple sets of diverse behaviours can develop naturally and rapidly, providing much greater scope for flexible behaviour-selection. The algorithm is tested extensively with a simulated e-puck robot that navigates around a maze by tracking colour. Results show that highly successful behaviour sets can be generated within about 25 minutes, and that much greater diversity can be obtained when multiple autonomous populations are used, rather than a single one.

Navegación de un robot móvil sobre terreno irregular con contacto de su brazo con el suelo

En esta tesis se aborda el problema de la navegabilidad de robots móviles sobre terrenos irregulares, los cuales poseen diferentes inclinaciones y variedad de obstáculos. Este tema constituye actualmente una línea de investigación activa dirigida al desarrollo de nuevos robots y, adicionalmente, enfocada al desarrollo de estrategias de navegación eficientes y con el mínimo riesgo de inutilización. En primer lugar se desarrolló el robot móvil Lázaro para navegar en este tipo de terrenos, el cual posee un brazo articulado con una rueda como efector final. Esta rueda le permite al brazo mantener un punto de contacto adicional con el suelo que puede ayudar al robot a compensar situaciones de inestabilidad y sobrepasar algunos obstáculos que pudieran presentarse en estos entornos. Posteriormente, se desarrollaron tres medidas cuantitativas que permiten evaluar la navegabilidad de cualquier robot móvil cuando transita sobre terreno irregular. Estas tres medidas son: un índice de estabilidad, el cual evalúa la propensión al vuelco; un índice de direccionamiento, el cual evalúa la disponibilidad del robot para direccionarse y seguir una trayectoria dada y, por último, un índice de deslizamiento, el cual evalúa la propensión del robot a deslizarse hacia abajo cuando se desplaza sobre superficies inclinadas. Finalmente, se definieron un conjunto de maniobras que puede ejecutar Lázaro y que están dirigidas a garantizar la navegación cuando el robot se desplaza sobre superficies inclinadas o cuando debe sobrepasar obstáculos tales como escalones, rampas o zanjas. Todas las estrategias diseñadas se fundamentan en el uso del brazo como herramienta adicional que posee el robot para mejorar su navegabilidad.

TORP: The Open Robot Project A Framework for Module-Based Robots

The development of robots has shown itself as a very complex interdisciplinary research field. The predominant procedure for these developments in the last decades is based on the assumption that each robot is a fully personalized project, with the direct embedding of hardware and software technologies in robot parts with no level of abstraction. Although this methodology has brought countless benefits to the robotics research, on the other hand, it has imposed major drawbacks: (i) the difficulty to reuse hardware and software parts in new robots or new versions; (ii) the difficulty to compare performance of different robots parts; and (iii) the difficulty to adapt development needs-in hardware and software levels-to local groups expertise. Large advances might be reached, for example, if physical parts of a robot could be reused in a different robot constructed with other technologies by other researcher or group. This paper proposes a framework for robots, TORP (The Open Robot Project), that aims to put forward a standardization in all dimensions (electrical, mechanical and computational) of a robot shared development model. This architecture is based on the dissociation between the robot and its parts, and between the robot parts and their technologies. In this paper, the first specification for a TORP family and the first humanoid robot constructed following the TORP specification set are presented, as well as the advances proposed for their improvement.

Mimicking the behaviour of idiotypic AIS robot controllers using probabilistic systems

Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techniques that rely on reinforcement learning only. This is thought to be a result of intelligent behaviour selection on the part of the idiotypic robot. In this paper an attempt is made to imitate idiotypic dynamics by creating controllers that use reinforcement with a number of different probabilistic schemes to select robot behaviour. The aims are to show that the idiotypic system is not merely performing some kind of periodic random behaviour selection, and to try to gain further insight into the processes that govern the idiotypic mechanism. Trials are carried out using simulated Pioneer robots that undertake navigation exercises. Results show that a scheme that boosts the probability of selecting highly-ranked alternative behaviours to 50% during stall conditions comes closest to achieving the properties of the idiotypic system, but remains unable to match it in terms of all round performance.