Exploration is an important aspect of robotics, whether it is for mapping, rescue missions or path planning in an unknown environment. Frontier Exploration planning (FEP) and Receding Horizon Next-Best-View planning (RH-NBVP) are two different approaches with different strengths and weaknesses. FEP explores a large environment consisting of separate regions with ease, but is slow at reaching full exploration due to moving back and forth between regions. RH-NBVP shows great potential and efficiently explores individual regions, but has the disadvantage that it can get stuck in large environments not exploring all regions. In this work we present a method that combines both approaches, with FEP as a global exploration planner and RH-NBVP for local exploration. We also present techniques to estimate potential information gain faster, to cache previously estimated gains and to exploit these to efficiently estimate new queries. ; FACT (SSF) ; WASP


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Efficient Autonomous Exploration Planning of Large Scale 3D-Environments


    Beteiligte:
    Selin, Magnus (Autor:in) / Tiger, Mattias (Autor:in) / Duberg, Daniel (Autor:in) / Heintz, Fredrik (Autor:in) / Jensfelt, Patric (Autor:in)

    Erscheinungsdatum :

    2019-01-01


    Anmerkungen:

    ISI:000459538100069



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629