Autonomous driving trajectory planning solution for U-Turn scenario
Structured Prediction Helps 3D Human Motion Modelling - ICCV '19
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
Excercises and examples from the Probabilistic Robotics book by Thrun, Burgard, and Fox.
Implementing Unscented Kalman Filter in C++ using Eigen library for a self-driving car
Unscented Kalman Filters
Add a description, image, and links to the motion-models topic page so that developers can more easily learn about it.
To associate your repository with the motion-models topic, visit your repo's landing page and select "manage topics."