Canal-U

Inria

4. Perception and Situation Awareness and Decision Making

Contents of this fourth part:

4.1. Robot Perception for Dynamic environments: Outline & DP-Grids concept
4.2. Dynamic Probabilistic Grids – Bayesian Occupancy Filter concept
4.3. Dynamic Probabilistic Grids – Implementation approaches
4.4. Object level Perception functions (SLAM + DATMO)
4.5. Detection and Tracking of Mobile Objects – Problem & Approaches
4.6. Detection and Tracking of Mobile Objects – Model & Grid based approaches
4.7. Embedded Bayesian Perception & Short-term collision risk (DP-Grid level)
4.8. Situation Awareness – Problem statement & Motion / Prediction Models
4.9. Situation Awareness – Collision Risk Assessment & Decision (Object level)

• Sciences de l’ingénieur

  Vidéocours

  8 min

  LABEL UNT

  
  

  4.1. Robot Perception for Dynamic environments: Outline & DP-Grids concept

• Sciences de l’ingénieur

  Vidéocours

  8 min

  LABEL UNT

  
  

  4.2. Dynamic Probabilistic Grids – Bayesian Occupancy Filter concept

• Sciences de l’ingénieur

  Vidéocours

  7 min

  LABEL UNT

  
  

  4.3. Dynamic Probabilistic Grids – Implementation approaches

• Sciences de l’ingénieur

  Vidéocours

  7 min

  LABEL UNT

  
  

  4.4. Object level Perception functions (SLAM + DATMO)

• Sciences de l’ingénieur

  Vidéocours

  7 min

  LABEL UNT

  
  

  4.5. Detection and Tracking of Mobile Objects – Problem & Approaches

• Sciences de l’ingénieur

  Vidéocours

  7 min

  LABEL UNT

  
  

  4.6. Detection and Tracking of Mobile Objects – Model & Grid based approaches

• Sciences de l’ingénieur

  Vidéocours

  7 min

  LABEL UNT

  
  

  4.7. Embedded Bayesian Perception & Short-term collision risk (DP-Grid level)

• Sciences de l’ingénieur

  Vidéocours

  8 min

  LABEL UNT

  
  

  4.8. Situation Awareness – Problem statement & Motion / Prediction Models

• Sciences de l’ingénieur

  Vidéocours

  10 min

  LABEL UNT

  
  

  4.9. Situation Awareness – Collision Risk Assessment & Decision (Object level)