HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems
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Updated
Nov 16, 2023 - Python
HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems
State estimation and filtering algorithms in Go
Accelerating Monte Carlo methods for Bayesian inference in dynamical models
This project implements grid-based FastSLAM1.0 and FastSLAM2.0 algorithms to solve SLAM problem in a simulated environment.
SLAM navigation on simplified scenario (FastSLAM implementation using Python) based on Particle Filter (Sequential Monte Carlo). What happens when the visual support of a drone is missing?
A data assimilation experiment with the DALEC ecosystem model
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables
Simultaneous State Estimation and Dynamics Learning from Indirect Observations.
Experiments for online learning and data assimilation for time series data.
Particle Filter estimators using C++ Multibody Dinamics library Simbody
Hybrid Extended Kalman Filter and Particle Filter. Graded project for the ETH course "Recursive Estimation".
Correlated pseudo-marginal Metropolis-Hastings using quasi-Newton proposals
Kidnapped Vehicle (project 6 of 9 from Udacity Self-Driving Car Engineer Nanodegree)
Localization in a static map, planning in a local map.
Using a 2-dimensional Particle Filter to localize a vehicle
Android applications for SmartPhoneSensing course for indoor localization
Bayesian Particle Learning models in R
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