Study and application of motion measurement methods by means of opto-electronics systems -
Studio e applicazione di metodi di misura del moto mediante sistemi opto-elettronici
This thesis addresses the problem of localizing a vehicle in unstructured environments through on-board instrumentation that does not require infrastructure modifications.
Two widely used opto-electronic systems which allow for non-contact measurements have been chosen: camera and laser range finder.
Particular attention is paid to the definition of a set of procedures for processing the environment information acquired with the instruments in order to provide both accuracy and robustness to measurement noise.
An important contribute of this work is the development of a robust and reliable algorithm for associating data that has been integrated in a graph based SLAM framework also taking into account uncertainty thus leading to an optimal vehicle motion estimation.
Moreover, the localization of the vehicle can be achieved in a generic environment since the developed global localization solution does not necessarily require the identification of landmarks in the environment, neither natural nor artificial.
Part of the work is dedicated to a thorough comparative analysis of the state-of-the-art scan matching methods in order to choose the best one to be employed in the solution pipeline.
In particular this investigation has highlighted that a dense scan matching approach can ensure good performances in many typical environments.
Several experiments in different environments, also with large scales, denote the effectiveness of the global localization system developed.
While the laser range data have been exploited for the global localization, a robust visual odometry has been investigated.
The results suggest that the use of camera can overcome the situations in which the solution achieved by the laser scanner has a low accuracy.
In particular the global localization framework can be applied also to the camera sensor, in order to perform a sensor fusion between two complementary instrumentations and so obtain a more reliable localization system.
The algorithms have been tested for 2D indoor environments, nevertheless it is expected that they are well suited also for 3D and outdoors
