Risk Estimation in Robotics and the Impact of Human Behaviour

Within this chapter the emerging topic of automated risk assessment in a domestic scene is discussed, state of the art techniques are reviewed followed by developed methodologies which focus on safer human and robotic interactions with an environment. By using the risk estimation framework, the notion of a quantitative risk score is presented. Hazards within a scene are evaluated and measured using risk elements which provide a numeric representation of specific types of risk. Emphasis is given to the concept of risk as a result of interaction with an environment, specifically whether human or robotic actions in a scene can effect overall risk. To this end, techniques which simulate human or robotic behaviour with regard to risk in an environment are reviewed. Specifically the ideas of interaction and visibility are addressed defining risk in terms of areas within a scene that are visited most often and which are least visible. As with any behaviour simulation techniques, validation of their accuracy is required and a number of simulation evaluation techniques are reviewed. Finally a conclusion as to the current state of automated risk assessment is given, with a brief look at the future of the research area

Estudio exploratorio de imágenes termográficas de la termorregulación de la mano mediante operadores espacio temporales de textura

En este proyecto se realiza un análisis exploratorio de la termorregulación de la mano en sujetos sanos, utilizando descriptores espacio-temporales de textura en secuencias de imágenes termográficas. Se caracterizan varias regiones de interés de las manos en las secuencias de imágenes, utilizando intensidades de píxel, evoluciones de ángulos de gradiente, y mediante los descriptores 3DHOG y Volumetric Local Binary Patterns (VLBP). Se obtiene un vector de características al registrar los valores de alguno de estos descriptores, en la misma ubicación espacial dentro de las manos, a lo largo del tiempo. Utilizando análisis de componentes principales y clustering se puede identificar que, la región distal (cercana a la punta) de los dedos, exhibe una termorregulación diferente a la región proximal (más cercana a la base) de los dedos. Dependiendo de cómo los descriptores considerados permiten ver estas diferencias en la termorregulación, se argumenta sobre su viabilidad en escenarios de análisis automático de la termorregulación de la mano.Ingeniero de Sistemaspregrad

Scene analysis and risk estimation for domestic robots, security and smart homes

The evaluation of risk within a scene is a new and emerging area of research. With the advent of smart enabled homes and the continued development and implementation of domestic robotics, the platform for automated risk assessment within the home is now a possibility. The aim of this thesis is to explore a subsection of the problems facing the detection and quantification of risk in a domestic setting. A Risk Estimation framework is introduced which provides a flexible and context aware platform from which measurable elements of risk can be combined to create a final risk score for a scene. To populate this framework, three elements of measurable risk are proposed and evaluated: Firstly, scene stability, assessing the location and stability of objects within an environment through the use of physics simulation techniques. Secondly, hazard feature analysis using two specifically designed novel feature descriptors (3D Voxel HOG and the Physics Behaviour Feature) which determine if the objects within a scene have dangerous or risky properties such as blades or points. Finally, environment interaction, which uses human behaviour simulation to predict human reactions to detected risks and highlight areas of a scene most likely to be visited. Additionally methodologies are introduced to support these concepts including: a simulation prediction framework which reduces the computational cost of physics simulation, a Robust Filter and Complex Adaboost which aim to improve the robustness and training times required for hazard feature classification models. The Human and Group Behaviour Evaluation framework is introduced to provide a platform from which simulation algorithms can be evaluated without the need for extensive ground truth data. Finally the 3D Risk Scenes (3DRS) dataset is introduced, creating a risk specific dataset for the evaluation of future domestic risk analysis methodologies