KaNaRiA - Kognitionsbasierte, autonome Navigation am Beispiel des Ressourcenabbaus im All KaNaRiA_Icon.png

KaNaRiA (from its German acronym: Kognitionsbasierte, autonome Navigation am Beispiel des Ressourcenabbaus iAll) is a joint venture of the University of Bremen and the Universität der Bundeswehr in Munich financed by the German Aerospace Centre (DLR - Deutsches Zentrum für Luft- und Raumfahrt).

The project comprises two major goals:

  • To perform a feasibility study of an autonomous asteroid mining mission
  • To build a software mission simulator to serve as platform for the development, test and verification of autonomous spacecraft navigation algorithm

The extraction of asteroid resources is of high interest for a great number of upcoming deep space missions aiming at a combined industrial, commercial and scientific utilization of space. The main technology driver enabling complex mission concepts in deep space is on-board autonomy. Such mission concepts generally include long cruise phases, multi-body fly-bys, planetary approach and rendezvous, orbiting in a-priori unknown dynamic environments, controlled descent, precise soft landing, docking or impacting, surface navigation or hopping.

9_Kanaria_LiDAR_asteroid.png

In KaNaRiA the focus is set on an asteroid mining mission scenario. The fundamental scope of the project is to design a spacecraft autonomous navigation system with decision capabilities inspired on biological and cognitive-based strategies.

The Professorship of Navigation is in charge of the design of the KaNaRiA spacecraft navigation subsystem including:

  • instrumentation,
  • on-board orbit and attitude determination algorithms,
  • on-board inertial and relative navigation and
  • dynamic characterization of the target asteroid based on on-board available information.

 

 

Contact: Daniela Sanchez
Funded by: DLR (FKZ: 50 NA 1319)
Duration: 01.10.2013 – 30.09.2017
Project partners:

University of Bremen

  • Insitut Kognitive Neuroinformatik
  • Institut Computergrafik und Virtuelle Realität
  • Institut Optimierung und Optimale Steuerung