Qualitative kinematics of planar robots: Intelligent connection

AbstractThis paper proposes a qualitative representation for robot kinematics in order to close the gap, raised by the perception–action problem, with a focus on intelligent connection of qualitative states to their corresponding numeric data in a robotic system. First, qualitative geometric primitives are introduced by combining a qualitative orientation component and qualitative translation component using normalisation techniques. A position in Cartesian space can be mathematically described by the scalable primitives. Secondly, qualitative robot kinematics of an n-link planar robot is derived in terms of the qualitative geometry primitives. Finally, it shows how to connect quantitativeness and qualitativeness of a robotic system. On the one hand, the integration of normalisation and domain knowledge generates normalised labels to introduce the meaningful parameters into the proposed representation. On the other hand, the normalised labels of this representation can be converted to a quantitative description using aggregation operators, whose numeric outputs can be used to generate desired trajectories based on mature interpolation techniques

Qualitative Process Analysis : Theoretical Requirements and Practical Implementation in Naval Domain

Understanding complex behaviours is an essential component of everyday life, integrated into daily routines as well as specialised research. To handle the increasing amount of data available from (logistic) dynamic scenarios, analysis of the behaviour of agents in a given environment is becoming more automated and thus requires reliable new analytical methods. This thesis seeks to improve analysis of observed data in dynamic scenarios by developing a new model for transforming sparse behavioural observations into realistic explanations of agent behaviours, with the goal of testing that model in a real-world maritime navigation scenario