0000duck / ai-robotics-udacity

概率推理、规划和搜索、定位、跟踪和控制probabilistic inference, planning and search, localization, tracking and control

CS373: Artificial Intelligence for Robotics | Programming a Robotic 🤖 Car 🚗

A Udacity Course instructed by Sebastian Thrun

Course Description

Learn how to program all the major systems of a robotic car from the leader of Google and Stanford's autonomous driving teams. This class provides the gist of many essential robotic stacks, including: probabilistic inference, planning and search, localization, tracking and control. Along with insightful lectures, there are many interesting problems and a challenging final project.

This course is offered as part of the Georgia Tech Masters in Computer Science. The updated course includes a final project, where you must chase a runaway robot that is trying to escape!

THIS IS MY REPOSITORY FOR THE COURSE

By Xuan Khai Nguyen

Below are some pictures (some are animations) from my programs:

1. Navigating through a maze by A* planning, path smoothing, and PID controller (twiddling for the best control parameters)

2. Similar setup, adding particle filter to deal with measurement noise

3. This is the picture from Part 4 of the Final Project (using Extended Kalman Filter and intercept algorithm):

There are detailed comments in each program, do not hesitate to ask if you are not clear. Please, give me a ⭐ if you see it useful.

I have consulted several sources, especially on the Udacity discussion forum. So, feel free to use it as a reference. Hope to receive your feedback.