Appearance-based mapping and localization using feature stability histograms for mobile robot navigation

• Autores: Eval Bladimir Bacca Cortes
• Directores de la Tesis: Joaquim Salvi Mas (dir. tes.), Xavier Cufí i Soler (dir. tes.)
• Lectura: En la Universitat de Girona ( España ) en 2012
• Idioma: inglés
• Tribunal Calificador de la Tesis: El Mustapha Mouaddib (presid.), Pere Ridao Rodríguez (secret.), Pascal Vasseur (voc.), José Jesús Guerrero Campo (voc.), Radu Orghidan (voc.)
• Materias:
  • Ciencias tecnológicas
    • Tecnología electrónica
      • Dispositivos láser
• Enlaces
  • Tesis en acceso abierto en: TDX
• Resumen

  • This work proposes an appearance-based SLAM method whose main contribution is the Feature Stability Histogram (FSH). The FSH is built using a voting schema, if the feature is re-observed, it will be promoted; otherwise it progressively decreases its corresponding FSH value. The FSH is based on the human memory model to deal with changing environments and long-term SLAM. This model introduces concepts of Short-Term memory (STM), which retains information long enough to use it, and Long-Term memory (LTM), which retains information for longer periods of time. If the entries in the STM are rehearsed, they become part of the LTM (i.e. they become more stable). However, this work proposes a different memory model, allowing to any input be part of the STM or LTM considering the input strength. The most stable features are only used for SLAM. This innovative feature management approach is able to cope with changing environments, and long-term SLAM.