In a mobile robotic system, the interaction with the surrounding environment is essential in order to complete tasks such as localisation and mapping. This interaction can only be conducted by means of sensors that permit the accumulation of a large amount of information from several sources. However, this information is useless without adequate interpretation; thus, in order to accurately determine the positioning of the robot, it is necessary to identify and characterise landmarks in the environment required to serve as anchoring points for both localisation and mapping. Having constructed the map, an accurate analysis of the information gathered is vital. In this manner, this work is focused on two main aspects of any mobile robotic system: first, the detection and characterisation of highly descriptive landmarks by using image and point cloud processing techniques; and second, the geometrical and spatial analysis of the information gathered from the environment. For the former, two novel techniques based on image processing and geometrical analysis are presented; for the latter, a guaranteed technique for the parameter estimation of primitive shapes using interval analysis is proposed.