State Estimation in Dynamical Robotic System with Non-Gaussian Noise
State estimation is critical for robot operation. Most estimation algorithms assume that the robotic sensor measurements are contaminated by Gaussian noise. However, in practical applications, the noise is often non-Gaussian, heavy-tailed, or even multi-modal. In this thesis, we develop algorithms t...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2024
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| Online Access: | https://hdl.handle.net/1721.1/157096 |