Basics of Mobile Robotics: Uncertainties

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Explores the use of inertial sensors for gait analysis and wearable systems.

Covers low power sensor technology for IoT and wearables, focusing on activity sensors based on MEMS and biosignals.

Introduces the rigorous approach to sensor fusion for modern applications.

Covers the theory and application of Kalman Filters for estimation and localization in robotics.

Explores error sources in odometry, sensor fusion, feature-based localization, and the Kalman Filter algorithm.

Explores sensor technologies in MEMS, focusing on pressure sensors, accelerometers, and gyroscopes, and highlights the significance of sensor fusion.

Covers the principles of inertial sensors and drift removal techniques.

Covers scaling laws in micro/nanomechanical devices and explores diverse MEMS applications.

Explores Kalman filters, flocking behaviors, and decentralized control in distributed intelligent systems.

Discusses the design and importance of flexible guides in microtechnology, highlighting their benefits and applications in MEMS devices.