Context classification for service robots

This dissertation presents a solution for environment sensing using sensor fusion techniques and a context/environment classification of the surroundings in a service robot, so it could change his behavior according to the different rea-soning outputs. As an example, if a robot knows he is outdoors, in a field environment, there can be a sandy ground, in which it should slow down. Contrariwise in indoor environments, that situation is statistically unlikely to happen (sandy ground). This simple assumption denotes the importance of context-aware in automated guided vehicles

Context Spaces Architectural Framework" presented at

Context-Aware Computing is a paradigm where context-aware applications, use acquired knowledge, related to a set of environmental states and attributes, to determine and adapt the applications behavior at runtime. Presented in this paper is a context-aware architectural framework, named “Context Spaces”. The context spaces framework enables the development and research of context-aware applications by mitigating common issues associated with dynamic environments. The framework components include a conceptual model, a protocol Application Message Interface for space based-distributed information sharing, and a method for context sharing between spaces called context acquisition. 1