01
Unit 1: Navigation Fundamentals and Localization
Mobile robot kinematics (differential drive, Ackermann steering), Odometry error accumulation and correction, Monte Carlo Localization (MCL/particle filters), Adaptive Monte Carlo Localization (AMCL), Extended Kalman Filter (EKF) for state estimation, UKF and information filters, Sensor fusion architectures (loose/tight coupling).
02
Unit 2: Simultaneous Localization and Mapping (SLAM)
SLAM problem formulation (chicken-egg problem), EKF-SLAM and covariance management, Graph-SLAM (pose graph optimization), FastSLAM (Rao-Blackwellized particle filters), LiDAR-based SLAM (Gmapping, Cartographer, LOAM), Visual SLAM (ORB-SLAM3, DSO), Loop closure detection and bundle adjustment.
03
Unit 3: Global Path Planning
Configuration space and environment modeling, Cell decomposition (trapezoidal, Boustrophedon), Potential fields (attractive/repulsive), Sampling-based planners (RRT, RRT*, Informed RRT*), Lattice planners and anytime algorithms, A* and variants (D*, Anytime D*, Field D*), Hybrid A* for non-holonomic constraints.
04
Unit 4: Local Path Planning and Collision Avoidance
Dynamic Window Approach (DWA), Velocity Obstacles (VO), Reciprocal Velocity Obstacles (RVO), Timed Elastic Bands (TEB), Model Predictive Control (MPC) for trajectory tracking, Pure pursuit and Stanley controllers, Emergency obstacle avoidance (reactive behaviors), Risk-aware planning and chance constraints.
05
Unit 5: ROS Navigation Stack and Multi-Robot
ROS nav2 stack architecture (Planner Server, Controller Server, BT Navigator), Costmaps (global/local, static/dynamic layers), Nav2 Behavior Trees for mission planning, Multi-robot coordination (CBBA, consensus algorithms), Decentralized planning (conflict-based search, prioritized planning), Fleet management and task allocation.