Visual Navigation in Unknown Environments

dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.author
Vidal Calleja, Teresa Alejandra
dc.date.accessioned
2011-04-12T15:09:47Z
dc.date.available
2007-09-10
dc.date.issued
2007-07-13
dc.date.submitted
2007-07-19
dc.identifier.isbn
9788469083314
dc.identifier.uri
http://www.tdx.cat/TDX-0719107-100000
dc.identifier.uri
http://hdl.handle.net/10803/6197
dc.description.abstract
Navigation in mobile robotics involves two tasks, keeping track of the robot's position and moving according to a control strategy. In addition, when no prior knowledge of the environment is available, the problem is even more difficult, as the robot has to build a map of its surroundings as it moves. These three problems ought to be solved in conjunction since they depend on each other. <br/>This thesis is about simultaneously controlling an autonomous vehicle, estimating its location and building the map of the environment. The main objective is to analyse the problem from a control theoretical perspective based on the EKF-SLAM implementation. <br/>The contribution of this thesis is the analysis of system's properties such as observability, controllability and stability, which allow us to propose an appropriate navigation scheme that produces well-behaved estimators, controllers, and consequently, the system as a whole. <br/>We present a steady state analysis of the SLAM problem, identifying the conditions that lead to partial observability. It is shown that the effects of partial observability appear even in the ideal linear Gaussian case. This indicates that linearisation alone is not the only cause of SLAM inconsistency, and that observability must be achieved as a prerequisite to tackling the effects of linearisation. Additionally, full observability is also shown to be necessary during diagonalisation of the covariance matrix, an approach often used to reduce the computational complexity of the SLAM algorithm, and which leads to full controllability as we show in this work.<br/>Focusing specifically on the case of a system with a single monocular camera, we present an observability analysis using the nullspace basis of the stripped observability matrix. The aim is to get a better understanding of the well known intuitive behaviour of this type of systems, such as the need for triangulation to features from different positions in order to get accurate relative pose estimates between vehicle and camera. Through characterisation the unobservable directions in monocular SLAM, we are able to identify the vehicle motions required to maximise the number of observable states in the system. <br/>When closing the control loop of the SLAM system, both the feedback controller and the estimator are shown to be asymptotically stable. Furthermore, we show that the tracking error does not influence the estimation performance of a fully observable system and viceversa, that control is not affected by the estimation. Because of this, a higher level motion strategy is required in order to enhance estimation, specially needed while performing SLAM with a single camera. Considering a real-time application, we propose a control strategy to optimise both the localisation of the vehicle and the feature map by computing the most appropriate control actions or movements. The actions are chosen in order to maximise an information theoretic metric. Simulations and real-time experiments are performed to demonstrate the feasibility of the proposed control strategy.
eng
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
Universitat Politècnica de Catalunya
dc.rights.license
ADVERTIMENT. L'accés als continguts d'aquesta tesi doctoral i la seva utilització ha de respectar els drets de la persona autora. Pot ser utilitzada per a consulta o estudi personal, així com en activitats o materials d'investigació i docència en els termes establerts a l'art. 32 del Text Refós de la Llei de Propietat Intel·lectual (RDL 1/1996). Per altres utilitzacions es requereix l'autorització prèvia i expressa de la persona autora. En qualsevol cas, en la utilització dels seus continguts caldrà indicar de forma clara el nom i cognoms de la persona autora i el títol de la tesi doctoral. No s'autoritza la seva reproducció o altres formes d'explotació efectuades amb finalitats de lucre ni la seva comunicació pública des d'un lloc aliè al servei TDX. Tampoc s'autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant als continguts de la tesi com als seus resums i índexs.
dc.source
TDX (Tesis Doctorals en Xarxa)
dc.subject
mapping
dc.subject
localization
dc.subject
mobile robotics
dc.subject
navigation
dc.subject
control
dc.subject
vision
dc.subject
SLAM
dc.subject
unknown environments
dc.title
Visual Navigation in Unknown Environments
dc.type
info:eu-repo/semantics/doctoralThesis
dc.type
info:eu-repo/semantics/publishedVersion
dc.subject.udc
004
cat
dc.contributor.director
Sanfeliu, Alberto
dc.contributor.codirector
Andrade-Cetto, Juan
dc.rights.accessLevel
info:eu-repo/semantics/openAccess
dc.identifier.dl
B.48081-2007


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