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Autonomous driving trajectory planning solution for U-Turn scenario
This repository contains solution for SLAM lectures taught by Claus Brenner on YouTube.
Working on five computer vision tasks (optical flow, mean-shift tracking, correlation filter tracking, advanced tracking, and long-term tracking) using the programming language Python.
Implement SLAM, a robust method for tracking an object over time and mapping out its surrounding environment using elements of probability, motion models, linear algerbra.
Kidnapped Vehicle (project 6 of 9 from Udacity Self-Driving Car Engineer Nanodegree)
Extended Kalman Filters
Unscented Kalman Filters
Excercises and examples from the Probabilistic Robotics book by Thrun, Burgard, and Fox.