Radu Mariescu-Istodor | 🚙Self-driving Car🔎ZOOMING🔎 @Radu | Uploaded 10 months ago | Updated 1 hour ago
Easter Egg found by Inosuke.
🚙Demo App 🚙
radufromfinland.com/projects/virtualworld
(you may need to clear cache: Ctrl + F5)
🎓Course🎓
youtube.com/playlist?list=PLB0Tybl0UNfZtY5IQl1aNwcoOPJNtnPEO
❓Hidden Features found so far❓
youtube.com/playlist?list=PLB0Tybl0UNfaINYqDw3A2NqPCsv8XEVQv
❄️Upcoming Self-driving car Q/A Live Stream❄️
youtube.com/live/Mj7gzO8GD3E
Easter Egg found by Inosuke.
🚙Demo App 🚙
radufromfinland.com/projects/virtualworld
(you may need to clear cache: Ctrl + F5)
🎓Course🎓
youtube.com/playlist?list=PLB0Tybl0UNfZtY5IQl1aNwcoOPJNtnPEO
❓Hidden Features found so far❓
youtube.com/playlist?list=PLB0Tybl0UNfaINYqDw3A2NqPCsv8XEVQv
❄️Upcoming Self-driving car Q/A Live Stream❄️
youtube.com/live/Mj7gzO8GD3E
![Self-driving car - No libraries - JavaScript course [Lecture 3]](https://i.ytimg.com/vi/2AKMSO2Gocs/hqdefault.jpg "Self-driving car - No libraries - JavaScript course [Lecture 3]
⭐️COURSE INTRODUCTION⭐️
Hi and welcome to the self-driving car (no libraries) JavaScript course.
You will learn to make a self-driving car simulation by implementing every component one by one. I will teach you how to implement the car driving mechanics, how to define the environment, how to simulate some sensors, how to detect collisions and how to make the car control itself using a neural network.
I will explain how artificial neural networks work, by comparing them with the real neural networks in our brain. I will teach you how to implement a neural network and how to visualize it so we can see it in action. You will also learn some optimization techniques to make our car smarter.
The entire system is quite complex, however, each component is relatively easy in and of itself. I made this course keeping in mind my high-school days back in Romania. So, the knowledge you get from school could be enough to follow along (depending on the curriculum).
We use JavaScript to implement this system and I will teach modern JavaScript techniques during this course, so, this course is perfect no matter if you want to become a software engineer or a machine learning specialist (like me - I have over 10 years research experience with machine learning).
⭐️LECTURE 3: ARTIFICIAL SENSORS⭐️
We implement a way for the car to sense the borders of the road so that it will later be able to avoid them. These sensors will work in the same way real proximity sensors do. We implement them using ray casting (a popular technique used in games so that AI characters can see you moving around). Our sensors will be customizable: you can change the number, length and spread of the rays.
⭐️MORE LINKS⭐️
- ThreeJS: https://threejs.org
⭐️CODE⭐️
Github: https://github.com/gniziemazity/Self-driving-car (3. Artificial sensors)
Use 2. Road definition if you plan to follow along!
My website: https://radufromfinland.com
⭐️ TABLE OF CONTENT ️⭐️
0:00 Course intro
1:13 The Sensor class
2:58 Casting the rays
5:40 Drawing the rays
11:19 Detecting the road borders
17:57 Drawing the sensor readings
19:43 Get intersection function")
![Coding with Radu [Extended Intro]](https://i.ytimg.com/vi/33YwKcVQ1vw/hqdefault.jpg "Coding with Radu [Extended Intro]
Extended intro song with all characters in the Raduverse :-)")
![A Virtual World - JavaScript Course: Lesson 4 / 11 [Polygon Operations in JavaScript]](https://i.ytimg.com/vi/3Aqe7Tv1jug/hqdefault.jpg "A Virtual World - JavaScript Course: Lesson 4 / 11 [Polygon Operations in JavaScript]
Welcome to the course where we build a self-driving car simulation in a virtual world. In this video well learn a technique using geometry to wrap the graph segments in what I like to call envelopes: polygons surrounding the segment in a certain way.
These envelopes have extra points that give them a smooth, rounded appearance. Well explore how to compute the union of these polygons to retain only the outer segments, resulting in visually pleasing and seamless road borders. Not only does this approach make your roads look more professional, but it also minimizes the number of clicks required in the editing process, making world building a satisfying endeavor.
Have Fun! :-) 🛣️
⭐PLAYLIST⭐
https://www.youtube.com/playlist?list=PLB0Tybl0UNfZtY5IQl1aNwcoOPJNtnPEO
⭐FINAL APP⭐
https://radufromfinland.com/projects/virtualworld
💻CODE💻
https://github.com/gniziemazity/virtual-world
3. Dynamic Viewport = follow along
4. Roads = code after this lesson
💻COPY CODE FROM HERE💻
https://radufromfinland.com/projects/virtualworld/CODES/lesson_4.js
⭐ALL PREREQUISITES⭐
https://www.youtube.com/playlist?list=PLB0Tybl0UNfZ3nnHVg8SJ4uK3R4QD6R0H
⭐My Video on 2D Vectors⭐
https://youtu.be/nzyOCd9FcCA
⭐My Video on Segment Intersection⭐
https://youtu.be/fHOLQJo0FjQ
⭐My Video on Interpolation⭐
https://youtu.be/J_puRs40GhM
☕Buy me a Coffee?☕
https://www.buymeacoffee.com/radum
⚡️Join this Channel⚡️
https://youtube.com/@radu/join
⭐Timestamps⭐
00:00 Introduction
01:07 Polygon Class
04:45 Polygon Envelopes
11:04 Roundness
16:45 World Class
20:35 Finding Intersections
35:22 Polygon Union
39:22 Point in Polygon Check
43:24 Styling")
![Dijkstras Algorithm in JavaScript [Understanding AI - Lesson 6 / 15]](https://i.ytimg.com/vi/3wux3N_2tk8/hqdefault.jpg "Dijkstras Algorithm in JavaScript [Understanding AI - Lesson 6 / 15]
PLAYLIST: https://www.youtube.com/playlist?list=PLB0Tybl0UNfYbL1vDNrfHoYOKf1Sn0A81
Dive into the world of pathfinding with JavaScript! In this video, we demystify the significance of Dijkstras algorithm and its role in making intelligent agents, like our self-driving car, more adept at finding their way to any location.
Whether youve been following the self-driving car codebase or not, fear not – were implementing almost everything from scratch, making it accessible to everyone. The codebase aids in testing and paves the way for future lessons on teaching cars to follow the path.
Join me in this informative session where I aim to help you grasp Dijkstras algorithm in the quickest way possible – pun intended! Well explore its core concepts and functionalities, laying the foundation for potential efficiency enhancements and advanced applications, such as computing the fastest path or incorporating real-time traffic information.
Share your learning experience in the comments – did coding Dijkstras algorithm make it clearer for you? Need a better explainer? Your feedback matters, and Im here to help you navigate the intricacies of this essential algorithm. Stay tuned for more insights and advanced lessons from my expertise in location-based applications. 🚗🗺️
💻CODE💻
https://github.com/gniziemazity/understanding_ai
Follow Along: 1. Starting Codebase
Code After This Lesson: 2. Dijkstra Part 1
💬DISCORD💬
discord.gg/gJFcF5XVn9
⭐LINKS⭐
Self-driving Car Course: https://www.youtube.com/playlist?list=PLB0Tybl0UNfYoJE7ZwsBQoDIG4YN9ptyY
#DijkstrasAlgorithm #UnderstandingAI #Pathfinding #JavaScriptCoding #AIPlayground #InteractiveLearning #LocationBasedApplications
⭐TIMESTAMPS⭐
00:00 Introduction
01:26 Graph Review
03:24 Starting to code Dijkstras Algorithm
09:08 Expanding
16:36 Backtracking
24:03 One-way Roads
27:00 Want More Dijkstra?")
