• DocumentCode
    2905568
  • Title

    Spatial partitioning for distributed agents driven by a line-of-sight navigation law in a spatiotemporal drift field

  • Author

    Bakolas, Efstathios

  • Author_Institution
    Dept. of Aerosp. Eng., Univ. of Texas at Austin, Austin, TX, USA
  • fYear
    2013
  • fDate
    17-19 June 2013
  • Firstpage
    2509
  • Lastpage
    2514
  • Abstract
    We consider the problem of characterizing a Voronoi-like partition of a two-dimensional Euclidean space which encodes information about the proximity relations between a team of spatially distributed aerial/marine vehicles and arbitrary points in the plane. In particular, a point in the plane is assigned to a particular vehicle if the latter can reach this point faster than any other vehicle from the same team. It is assumed that each vehicle is constrained to travel along the line-of-sight direction to its destination point in the presence of a spatiotemporal drift field, which is induced by, say, local winds/currents. We present an efficient scheme for the computation of the Voronoi-like partition which exploits the direct correspondence between the level sets of the Euclidean distance and those of the time-to-go by means of a bijective mapping. Next, we identify a number of important topological properties enjoyed by the generators and the cells of the partition. Finally, we present simulation results using data from real drift fields.
  • Keywords
    autonomous aerial vehicles; computational geometry; marine vehicles; multi-robot systems; path planning; Euclidean distance; Voronoi-like partition; bijective mapping; distributed agents; line-of-sight direction; line-of-sight navigation law; spatial partitioning; spatially distributed aerial-marine vehicles proximity relations; spatiotemporal drift field; topological properties; two-dimensional Euclidean space; Equations; Generators; Level set; Measurement; Navigation; Vectors; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2013
  • Conference_Location
    Washington, DC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-0177-7
  • Type

    conf

  • DOI
    10.1109/ACC.2013.6580211
  • Filename
    6580211