Descriptions
Autonomous robots: Non-holonomic motion planning algorithms, Movement Planning is an area of engineering that deals with calculating a path from a starting point to a destination while avoiding obstacles, for example using Google or Apple Maps. The large Most vehicles in today’s world (cars, boats, airplanes) are non-holonomic, meaning they have limited degrees of freedom of movement given the available space. For Instances, Think about pushing a car between adjacent parking spaces. The car cannot “slide” sideways into the second parking space. It must reverse and turn into place or drive around in a circular path. Given two Given arbitrary positions and directions on a map, the task is to find a uniform trajectory that satisfies the vehicle’s speed limits. This is achieved by using the Dubin path. In The CoursesLearn how to derive Dubin’s Path from first principles and implement and test the method on a task. Next, you’ll learn how to combine this theory with sampling-based motion planning algorithms. The next two tasks involve finding a path using RRT and RRT* with Dubin’s Path. lastThe final task will involve an incremental RRT using Dubins Path for a realistic roadmap scenario where the vehicle has limited information.
What you will learn
- Learn the Dubins Curve algorithm for smooth trajectory generation between two waypoints on a map.
- Compute a path using the Rapidly Exploring Random Trees (RRT) and RRT* algorithms in combination 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 is this course suitable for?
- Anyone interested in autonomy, robotics, algorithms and path planning.
Specifics of autonomous robots: Non-holonomic motion planning algorithms
- Editor: Udemy
- Teacher: Vinayak Deshpande
- Language: English
- Level: Beginner
- Number of courses: 23
- Duration: 3 hours and 21 minutes
Content of autonomous robots: Nonholonomic motion planning algorithms
Requirements
- No programming experience required. 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 available for the tasks.
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