AMCL on a Known Map

Key Insight

Localize a mobile robot within a known occupancy grid map using Adaptive Monte Carlo Localization (AMCL). By representing the robot's possible positions as a set of particles, the algorithm combines noisy wheel odometry with lidar scans to estimate the robot's pose. As the robot moves and detects features, the particle filter resamples to converge on the true location, dynamically adjusting the particle count to balance estimation accuracy with real-time computational constraints.