An Introduction to Sampling based Motion Planning Algorithms

🚦 Interested in self-driving cars and robotics? Then check out this course!

🚀 Course Title: An Introduction to Sampling based Motion Planning Algorithms
🧠 Course Instructor: Vinayak Deshpande

Welcome to the fascinating world of motion planning, where algorithms shape the paths of autonomous vehicles and robots! This course is your gateway into understanding the sophisticated mechanisms behind self-driving cars and advanced robotics. 🚗✨

What You'll Learn:

• Foundational Concepts: Dive deep into the core ideas of motion planning and how it's crucial for autonomous systems to navigate complex environments.

• RRT & RRT Algorithms:* Master the Rapidly Exploring Random Trees (RRT) and enhanced version RRT*, which are at the heart of many motion planning applications.

• Hands-On Experience: Implement these cutting-edge algorithms in Python, even if you're new to programming! 🧑‍💻

Course Structure:

• Essential Theory: We'll cover the theoretical underpinnings of RRT and RRT* algorithms, explaining how they differ from traditional search-based algorithms like A*.

• Practical Implementation: You'll get your hands dirty with 3 interactive assignments, where you'll see your algorithms come to life. 🛠️

Why This Course?

• Industry Relevance: Understand the practical applications of motion planning in real-world scenarios.

• Skill Development: Enhance your programming skills, particularly with Python, Numpy, and Matplotlib.

• Comprehensive Learning: From setting up your environment to implementing complex algorithms, you'll have all the tools you need for success. 🛠️

Course Requirements:

• Python 3.7 (installation guide provided)

• Numpy and Matplotlib libraries (essential for visualizing your path planning)

By the End of This Course, You Will:

• Have a solid understanding of the RRT based algorithms.

• Be able to generate paths consisting of waypoints between start and end locations in a given space, effectively avoiding obstacles.

• Understand how these algorithms contribute to real-world applications like self-driving cars and robotics.

Don't wait! Join us on this exciting journey into the world of motion planning with sampling based algorithms. Your future self, armed with these skills, will thank you for it. 🚀

Leave a Rating When You Finish: Your feedback is invaluable to improving the course and ensuring that it meets your learning needs.

I'm excited to guide you through this course and can't wait to see the paths you create! 🎓✨

Enroll now and let's embark on this journey together! 🎉