Mobile Robot Localisation and World Modeling in a Real-Time Software Architecture

The goal of autonomous mobile robotics is to build physical systems that can interact with environments not specifically structured for this purpose. Even if the applications that might exploit autonomous mobile robots are widespread, current technologies are still immature at satisfying the growing requests. For this reason, robot navigation constitutes one of the major trends in the current research on robotics. A precondition for a mobile robot to be autonomous is the ability to self-localise inside an environment. This precondition is dificult to satisfy when the robot does not exploit a map of the environment to localise itself. Current research investigates methods for map learning, based on the detection of natural features. These methods should allow a robot to self-localise inside the environment it is exploring, and contemporarily to build an incremental representation of the same environment. Research on these methods is still in progress. This is due to the fact that the problem they face is hard because of the following paradox: position estimation needs a model of the environment, and world modelling needs the robot position. \Which come first, the chicken or the egg?" Current research answers the question by proposing solution based upon the simultaneity of the activities. These kinds of approach are known under the SLAM (Simultaneous Localisation And Mapping) acronym, and support the idea that the two activities should be performed together. The aim of this work is to propose a novel approach based upon the concurrence of the two activities. This approach, named CLAM (Concurrent Localisation And Mapping), is founded upon the conjecture that a proper separation of concerns may help in breaking the loop of the \chicken and egg" problem. Localisation and Modelling, acting on different time scales, are mostly independent each other. Sometimes a synchronisation is needed, but controlled by an external and suitable strategy. We consider the CLAM system a time-sensitive one since it has to perform a number of different activities with multiple, dynamic, and interdependent temporal requirements. Furthermore, a CLAM system must be able to dynamically change the activities temporal requirements. To fulfill the goal we have to define and implement a general framework for the construction of time-sensitive systems. The framework, named Real-Time Performers, is composed by a reference architecture and a working implementation providing software engineers a consistent set of software modules to build time-sensitive systems. The architecture is based upon a novel methodology based on computational reflection, this methodology models the temporal behaviour of the computational system with a set of suitable architectural abstractions, reifying time related aspects of the system itself. The final result of this work consists in a real implementation of a system supporting the exploration activity of a robot equipped with an odometric system (for positioning) and a trinocular stereo system (for environment perception). CLAM principles and Real-Time Performers architecture have driven the design of this system. Finally, the resulting system has been developed exploiting Real-Time Performers framework.