Fundamentals of Mobile Robots, 5 cr

Core content

• Deterministic planning methods: dynamic programming, Dijkstra, A*
  
• Bayesian filtering
• Localization using Kalman filters and particle filters.
• Occupancy grid mapping
• Sensor technologies (LiDAR, Radar, Sonar, Leddar, IMU, GNSS, UWB), sensor models (LiDAR, Sonar, IMU) and their uncertainty
• Motion control: path smoothing, path following and trajectory tracking

Complementary knowledge

• planning under uncertainty: solving MDP
• mathematics of probabilities
• world models and representations
• state space models, state feedback

Specialist knowledge

• How to convert continuous real world to discrete world suitable for planners.
  POMDP
• Simultaneous Localization and Mapping