Tesi etd-02292008-163219 | 
    Link copiato negli appunti
  
    Tipo di tesi
  
  
    Tesi di dottorato di ricerca
  
    Autore
  
  
    BRACCI, ANDREA  
  
    URN
  
  
    etd-02292008-163219
  
    Titolo
  
  
    Cooperative control of autonomous vehicles
  
    Settore scientifico disciplinare
  
  
    ING-INF/04
  
    Corso di studi
  
  
    AUTOMATICA, ROBOTICA E BIOINGEGNERIA
  
    Relatori
  
  
    Relatore Prof. Innocenti, Mario
  
    Parole chiave
  
  - autonomous vehicles
 - cooperative control
 
    Data inizio appello
  
  
    12/06/2008
  
    Consultabilità
  
  
    Completa
  
    Riassunto
  
  This thesis deals with the mission management of a team of autonomous vehicles. The two main issues of the mission management are considered: the path-planning among obstacles, and the task-assignment.
In the context of path-planning a novel procedure based on a dynamic version of the Constrained Delaunay Triangulation (CDT) is proposed. This procedure takes advantage of the geometrical properties of the triangles in order to obtain obstacle-free paths with a low computational load.
In the context of task-assignment, two novel approaches are proposed. The former is based on a dynamic task clustering in order to obtain a less myopic view of the scenario. The latter is based on a dynamic task ranking, that is, a set of dynamic weights that the vehicles have for each task. The main advantages of the proposed procedures are the low computational cost and a full decentralization, together with a certain degree of optimality.
In the context of path-planning a novel procedure based on a dynamic version of the Constrained Delaunay Triangulation (CDT) is proposed. This procedure takes advantage of the geometrical properties of the triangles in order to obtain obstacle-free paths with a low computational load.
In the context of task-assignment, two novel approaches are proposed. The former is based on a dynamic task clustering in order to obtain a less myopic view of the scenario. The latter is based on a dynamic task ranking, that is, a set of dynamic weights that the vehicles have for each task. The main advantages of the proposed procedures are the low computational cost and a full decentralization, together with a certain degree of optimality.
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| Bracci_PhDThesis.pdf | 1.55 Mb | 
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