Udemy – Autonomous Robots: Nonholonomic Motion Planning Algorithms 2023-4

Udemy – Autonomous Robots: Nonholonomic Motion Planning Algorithms 2023-4 Downloadly IRSpace

Apr 17, 2025 - 13:48 Updated: Aug 17, 2025 - 13:04

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Udemy – Autonomous Robots: Nonholonomic Motion Planning Algorithms 2023-4

Autonomous Robots: Nonholonomic Motion Planning Algorithms, Motion planning is a field of engineering dealing with calculating a path from a start to a goal location whilst avoiding obstacles, for example using Google or Apple Maps. The vast majority of vehicles in today’s world i.e (cars, boats, planes) are non holonomic, meaning they have limited degrees of freedom of movement with respect to the available space. For instance, think of shifting a car between adjacent parking spots. The car cannot ‘slide’ sideways into the second parking spot. It has to reverse and turn in to the spot, or go around in a circular path. Given two arbitrary positions and headings on a map, the task is to find a smooth trajectory which satisfies the speed constraints of the vehicle. This is accomplished by using the Dubins Path. In this course, you will learn how to derive the Dubins Path from first principles and also implement and test the method via an assignment. Next, you will learn how to combine this theory with sampling based motion planning algorithms. The next two assignments will involve finding a path using RRT and RRT* with Dubins Path. Lastly, the final assignment will involve incremental RRT with Dubins Path for a realistic roadmap scenario, where the vehicle has limited information.

What you’ll learn

Learn the Dubins Curve algorithm for smooth trajectory generation between two waypoints on a map.
Calculate a path using the Rapidly Exploring Random Trees (RRT) and RRT* algorithms combined with Dubins curves.
Learn the basics of incremental path planning for real time applications.
Determine a path using Incremental RRT with Dubins curves, and analyze your results quantitatively.

Who this course is for

Anyone with an interest in autonomy, robotics, algorithms and path planning.

Specificatoin of Autonomous Robots: Nonholonomic Motion Planning Algorithms

Publisher : Udemy
Teacher : Vinayak Deshpande
Language : English
Level : Beginner
Number of Course : 23
Duration : 3 hours and 21 minutes

Content of Autonomous Robots: Nonholonomic Motion Planning Algorithms

Autonomous Robots_ Nonholonomic Motion Planning Algorithms

Requirements

No programming experience needed. I will teach you everything from scratch.
It is recommended that students have Python 3.9.x, Numpy 1.23.x and Matplotlib 3.x ready for the assignments.