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This lecture covers the concepts of finite state machines, their implementation in robotics, and the subsumption architecture. It discusses the use of conditions and sensors in state machines, as well as the hierarchical structure of subsumption architectures. The implementation details of both models are explored, including obstacle avoidance strategies and sensitivity-dependent behaviors. Additionally, the lecture addresses the limitations of reactive control in explaining animal behavior and introduces differential robot kinematics, path integration algorithms, and landmark-assisted localization.
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