Explore the Fascinating Field of AI and Robotics with CS7638

Table of Contents:

1. Introduction
2. Overview of CS7638: Artificial Intelligence for Robotics
3. Course Difficulty and Workload
4. Course Goals and Objectives
5. Instructional Team
6. Prerequisites for the Course
7. Grading Policy
8. Project Descriptions and Reviews 8.1 Asteroids Project 8.2 Mars Glider Project 8.3 PID Mini Project 8.4 Search Project 8.5 Gem Finder Project
9. Final Exam
10. Overall Impressions and Recommendations

A Comprehensive Review of CS7638: Artificial Intelligence for Robotics

Are you interested in diving into the world of artificial intelligence and robotics? Look no further! In this article, we will provide an in-depth review of a popular online course called CS7638: Artificial Intelligence for Robotics. Whether you're a beginner or have some prior experience in programming and math, this course offers a fantastic opportunity to explore the fascinating field of robotics and AI. Let's embark on this educational journey together!

Introduction

CS7638, also known as Artificial Intelligence for Robotics, is a course offered as part of Georgia Tech's online Masters in Computer Science program. In this course review, we will provide a detailed overview, discuss the course's difficulty and workload, introduce the instructional team, highlight the prerequisites, Outline the grading policy, and review the various projects and assignments. Finally, we will share our overall impressions and recommendations for taking this course.

Overview of CS7638: Artificial Intelligence for Robotics

CS7638 is designed to teach students fundamental concepts and techniques in robotics and artificial intelligence. Taught by the renowned Dr. Sebastian Thrun, leader of Google and Stanford's autonomous driving team, this course covers essential topics, including probabilistic inference, planning and search, localization, tracking, mapping, and control. The curriculum focuses on programming major systems of a robotic car, providing students with a hands-on experience in AI techniques for robotics.

Course Difficulty and Workload

When considering course difficulty, CS7638 has an average difficulty rating of three out of five, according to omscentral.com. The workload is estimated to be around 12.6 hours per week, which is reasonable for an online course. These numbers suggest that the course strikes a balance between challenging students without overwhelming them. The average course rating of 3.94 highlights that CS7638 is relatively well-liked among students in the program.

Course Goals and Objectives

The primary goal of CS7638 is to impart knowledge derived from the expertise of Dr. Sebastian Thrun and his team. With a focus on robotics, students will learn how to program the major systems of a robotic car and gain insights into artificial intelligence, including probabilistic inference, planning and search, localization, tracking, mapping, and control. These skills are invaluable for anyone interested in the field of robotics or AI.

Instructional Team

Dr. Sebastian Thrun, the course creator, brings his extensive experience and expertise in autonomous driving to the instructional videos. Although the pre-recorded lectures by Dr. Thrun are a bit dated, they still offer valuable insights. The instructional team is supported by Jay Summitt, who handles the logistics of the course. Additionally, numerous teaching assistants (TAs) are available to provide guidance and support throughout the course.

Prerequisites for the Course

Before enrolling in CS7638, it is essential to have some specific prerequisites. Firstly, programming experience, preferably in Python, is required. The course heavily relies on Python 3 for all assignments. Additionally, a strong understanding of linear algebra is recommended, as matrices play a significant role in the course concepts. While a strong understanding of probability is not mandatory, it proves beneficial for comprehending probabilistic inference techniques. Prior coursework in machine learning, computer vision, or robotics is helpful but not mandatory.

Grading Policy

The grading policy for CS7638 includes multiple components: problem sets and a syllabus quiz (20%), a PID mini-project (10%), four major projects – Asteroids, Mars Glider, Search, and Gem Finder – each worth 15% of the grade, and a final exam (10%). The great thing about the projects is that they can be submitted multiple times on Grade Scope, allowing students to improve their solutions based on feedback and ultimately achieve high scores. Students who score a perfect 100% on all other components before the final exam can even be exempted from taking the exam.

Project Descriptions and Reviews

CS7638 consists of several projects that provide hands-on experience in applying the learned concepts. Let's explore each of the projects briefly:

8.1 Asteroids Project

In the Asteroids project, students are tasked with creating a common filter to locate and predict the motion of asteroids in outer space. This project not only focuses on localization but also requires navigation through an asteroid field. The project offers a fun and visually appealing experience, as students get to witness their spacecraft weaving through the asteroids.

8.2 Mars Glider Project

The Mars Glider project introduces students to particle filters and their application in glider localization. Students must determine the glider's position on a map using altitude and ground distance measurements. The project also involves navigating the glider to a specific drop zone. This visually engaging project provides an opportunity to apply particle filter techniques in a realistic Scenario.

8.3 PID Mini Project

The PID mini-project is centered around proportional-integral-derivative (PID) controllers. Students are required to use a PID controller to regulate the thrust of a simulated turbo Pump in a rocket. This project focuses on maintaining a specific velocity and can be challenging due to the need for precise parameter tuning. While it may not be as visually appealing as other projects, the PID mini-project provides valuable insights into control systems.

8.4 Search Project

The Search project, named Warehouse, introduces students to search algorithms and their application in finding an optimal path to retrieve boxes in a warehouse. Divided into two parts – A* search and dynamic programming – this project offers an exciting opportunity to solve practical problems beyond robotics. While the visualization aspect is minimal, the project provides a rewarding experience in implementing efficient search algorithms.

8.5 Gem Finder Project

The final project, Gem Finder, focuses on simultaneous localization and mapping (SLAM). In this project, students must localize an agent following a series of movements and measurements. Additionally, the agent must Collect a list of Gems scattered throughout the world. This project does not provide a pre-defined map, adding an extra layer of complexity to the SLAM process. Overall, the Gem Finder project serves as a comprehensive culmination of the course's teachings.

Final Exam

The final exam in CS7638 consists of approximately 20 to 25 questions and accounts for 10% of the overall grade. The exam format includes multiple-choice questions and some free response questions that involve probability calculations and matrix operations. Students who have performed well on the projects and attained a high grade can potentially exempt themselves from taking the final exam.

Overall Impressions and Recommendations

In conclusion, CS7638: Artificial Intelligence for Robotics is an exciting course that offers a comprehensive introduction to the field. While the lectures provided by Dr. Thrun can be a bit superficial and slightly outdated, the materials provided by the TAs and Jay Summitt make up for it. The projects provide ample opportunities to apply the concepts learned, with the Asteroids and Mars Glider projects offering particularly enjoyable and visually appealing experiences. The course's grading policy allows students to submit projects multiple times, ensuring a fair assessment of their understanding. Overall, this course is highly recommended for anyone looking to explore the intersection of artificial intelligence and robotics.

Highlights:

• CS7638: Artificial Intelligence for Robotics is an online course offered by Georgia Tech.
• The course covers essential topics in robotics, including AI techniques and programming major systems of a robotic car.
• The course has an average difficulty rating, but the workload is manageable.
• Dr. Sebastian Thrun, a leader in autonomous driving, is the course creator.
• Prerequisites include programming experience in Python, knowledge of linear algebra, and some familiarity with probability.
• The course consists of projects that allow students to apply the concepts learned.
• The grading policy includes projects, a final exam, and other components.
• Overall, the course provides a valuable and engaging learning experience in robotics and AI.

FAQ:

Q: Is prior programming experience required for CS7638?

• Yes, programming experience is required, preferably in Python.

Q: Can I take this course if I have no background in robotics or AI?

• Absolutely! This course is designed to provide an introduction to the field, making it suitable for both beginners and those with prior experience.

Q: Are the projects in CS7638 challenging?

• The projects are designed to be challenging but manageable. The iterative submission process allows students to improve their solutions based on feedback.

Q: Can I exempt myself from taking the final exam?

• If you score a perfect 100% on all other components (projects, problem sets, etc.), you may be exempted from taking the final exam.

Resources:

• OMSCentral - Website providing reviews and ratings for courses in Georgia Tech's online Masters in Computer Science program.