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This chapter covers the core systems that enable autonomous robots — from how robots represent and reason about motion, to how they estimate their state, build maps, and integrate perception with action. The unifying narrative is building an autonomous robot that navigates an unknown environment. Each section contributes a piece of that system:
  • Kinematics & Dynamics — how robots are structured and move
  • State Estimation — how robots figure out where they are
  • SLAM — how robots build maps while localizing
  • Systems Integration — simulation, ROS, and bridging from simulation to real hardware

Kinematics & Dynamics

Configuration spaces, homogeneous coordinates, motion representations, and wheeled robot kinematics.

State Estimation

Recursive Bayesian estimation, Kalman filters, and probabilistic localization.

SLAM

Occupancy grid mapping and simultaneous localization and mapping.

Systems Integration

Gazebo simulation, ROS applications, and sim-to-real transfer.
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