Search algorithms | Probabilistic data structures
A rapidly exploring random tree (RRT) is an algorithm designed to efficiently search nonconvex, high-dimensional spaces by randomly building a space-filling tree. The tree is constructed incrementally from samples drawn randomly from the search space and is inherently biased to grow towards large unsearched areas of the problem. RRTs were developed by Steven M. LaValle and James J. Kuffner Jr.They easily handle problems with obstacles and differential constraints (nonholonomic and kinodynamic) and have been widely used in autonomous robotic motion planning. RRTs can be viewed as a technique to generate open-loop trajectories for nonlinear systems with state constraints. An RRT can also be considered as a Monte-Carlo method to bias search into the largest Voronoi regions of a graph in a configuration space. Some variations can even be considered stochastic fractals. RRTs can be used to compute approximate control policies to control high dimensional nonlinear systems with state and action constraints. (Wikipedia).
Searching a Tree - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Searching a Tree - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Igor Kortchemski: Condensation in random trees - Lecture 2
We study a particular family of random trees which exhibit a condensation phenomenon (identified by Jonsson & Stefánsson in 2011), meaning that a unique vertex with macroscopic degree emerges. This falls into the more general framework of studying the geometric behavior of large random dis
From playlist Probability and Statistics
Path Planning with A* and RRT | Autonomous Navigation, Part 4
See the other videos in this series: https://www.youtube.com/playlist?list=PLn8PRpmsu08rLRGrnF-S6TyGrmcA2X7kg This video explores some of the ways that we can use a map like a binary occupancy grid for motion and path planning. We briefly cover what motion planning means and how we can us
From playlist Autonomous Navigation
Random Forest Algorithm Clearly Explained!
Here, I've explained the Random Forest Algorithm with visualizations. You'll also learn why the random forest is more robust than decision trees. #machinelearning #datascience For more videos please subscribe - http://bit.ly/normalizedNERD Join our discord - https://discord.gg/39YYU93
From playlist Tree-Based Algorithms
Igor Kortchemski: Condensation in random trees - Lecture 3
We study a particular family of random trees which exhibit a condensation phenomenon (identified by Jonsson & Stefánsson in 2011), meaning that a unique vertex with macroscopic degree emerges. This falls into the more general framework of studying the geometric behavior of large random dis
From playlist Probability and Statistics
Igor Kortchemski: Condensation in random trees - Lecture 1
We study a particular family of random trees which exhibit a condensation phenomenon (identified by Jonsson & Stefánsson in 2011), meaning that a unique vertex with macroscopic degree emerges. This falls into the more general framework of studying the geometric behavior of large random dis
From playlist Probability and Statistics
Bi-Directional RRT Algorithm for Robot Manipulators | Motion Planning with the RRT Algorithm, Part 3
Industrial robots are designed to perform specific tasks and appropriate algorithms for perception, planning, and control. Watch the full video series: https://youtube.com/playlist?list=PLn8PRpmsu08qQorl_KLrSns9jI827aplS Pick and place automation, for example, can speed up the process of
From playlist Motion Planning Using RRT Algorithm
Introduction to Motion Planning Algorithms | Motion Planning with the RRT Algorithm, Part 1
Motion planning lets robots or vehicles plan an obstacle-free path from a start to goal state. Learn some popular motion planning algorithms, how they work, and their applicability in different scenarios. Watch the full video series: https://youtube.com/playlist?list=PLn8PRpmsu08qQorl_KLr
From playlist Motion Planning Using RRT Algorithm
Lecture 14 | MIT 6.832 Underactuated Robotics, Spring 2009
Lecture 14: Feasible motion planning Instructor: Russell Tedrake See the complete course at: http://ocw.mit.edu/6-832s09 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.832 Underactuated Robotics, Spring 2009
Morphing symmetric binary branching tree
A symmetric binary tree is obtained by applying certain affine linear transformations recursively to the leaves starting with a trunk of unit length. This video shows a scale factor given by the golden ratio (well, roughly 0.618) and morphs between various angles of rotation. To build yo
From playlist Fractals
Lester Mackey, Stanford University - Stanford Big Data 2015
Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/.
From playlist Big Data in Biomedicine Conference 2015
Why Human Evolution Matters: Crash Course Big History 204
This week on Crash Course Big History, Emily is talking about process of human evolution, and the knack for innovation that has allowed humans to become so dominant on the Earth. Human innovation, and the ability to build on those innovations generation after generation is what makes human
From playlist Big History 2
From one extreme to another: the statistics of extreme events - Jon Keating
One pleasure of mathematics is its capacity to connect seemingly unconnected problems, & to do it with just a few numbers & symbols. Mountain ranges, family trees, performance at the Olympic Games and Prime Numbers will all be joined by Jon Keating's mathematical thread in this Oxford Mat
From playlist Oxford Mathematics Public Lectures
Wolfram Physics Project: Working Session Tuesday, Nov. 3, 2020 [Combinators]
This is a Wolfram Physics Project working session on combinators. Originally livestreamed at: https://twitch.tv/stephen_wolfram Stay up-to-date on this project by visiting our website: http://wolfr.am/physics Check out the announcement post: http://wolfr.am/physics-announcement Find the
From playlist Wolfram Physics Project Livestream Archive
Christina Goldschmidt: Scaling limits of random trees and graphs - Lecture 2
HYBRID EVENT In the last 30 years, random combinatorial structures and their scaling limits have formed a flourishing area of research at the interface between probability and combinatorics. In this mini-course, I aim to show some of the beautiful theory that arises when considering scalin
From playlist Probability and Statistics
Binary tree traversal - breadth-first and depth-first strategies
See complete series on data structures here: http://www.youtube.com/playlist?list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P In this lesson, we have discussed algorithms for binary tree traversal. We have talked about breadth-first and depth-first strategies for tree traversal like level-order, p
From playlist Data structures
Intro to Machine Learning: Lesson 7
Today we'll finish off our "from scratch" random forest interpretation! We'll also briefly look at the amazing "cython" library that you can use to get the same speed as C code with minimal changes to your python code. Then we'll start on the next stage of our journey - gradient descent b
From playlist Introduction to Machine Learning for Coders
The Evolutionary Epic: Crash Course Big History #5
In which John Green, Hank Green, and Emily Graslie teach you about evolution. So, in the last 3.8 billion years, life on Earth has evolved from single-celled prokaryotes to the dizzying array of life we have today. So how did all this happen? We'll talk about Darwin, evolution, natural sel
From playlist Big History