English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 3h 35m | 617 MB
Use the A* (A-star) search algorithm to find the driving route between any two locations in New York City, just as Google Maps does
Path planning involves finding an optimal and viable path from the current location to the goal location. This is crucial for any robot that must move something in the real world, whether it’s a robotic arm or a self-driving car.
This course will get you up to speed with the A* algorithm that is one of the most fundamental robotics algorithms. A fun fact is that this algorithm was even used on the first general-purpose mobile robot – Shakey the Robot. You’ll go on to understand how to use Robotics to create a viable path from your start to end location. Next, you’ll start the search on a small grid between two lanes, and then gradually scale up to navigate between any two locations in New York City. As you progress, you will build on your knowledge of robotics and get hands-on with path planning. A dedicated section will also guide you through advanced heuristics.
By the end of this course, you will be well-versed with path planning and have the skills you need to use the A* algorithm to find the shortest driving path between two locations.
Learn
- Become well-versed with path planning
- Understand the concept of robotics
- Get to grips with advanced heuristics
Table of Contents
Introduction
1 Problem Setup
2 Simulator Setup
3 Conda Environments
4 Old Simulator Setup
5 Assignment 0 – Intro
BFS and DFS Grid World
6 BFS and DFS Intro
7 BFS and DFS Implementation
8 Assignment 1 – Intro
9 Assignment 1 – Solution
A Search Grid World
10 A Search Intro
11 Assignment 2 – Intro
12 Assignment 2 – Solution 1
13 Assignment 2 – Solution 2
A Search New York City
14 New York City Intro
15 Assignment 3 – Intro
16 Assignment 3 – Solution
A Search – Advanced Heuristics
17 Assignment 4 – Intro
18 Assignment 4 – Solution
Outro
19 Outro
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