Making a Drone Smarter With Motion Planning

This fully autonomous drone has an onboard computer ‘brain’, camera ‘eyes’, and an algorithm that generates the fastest path around unknown obstacles as they’re detected mid-flight. Everything is computed onboard with no need for a radio connection to the ground, making it completely immune to jamming.

GPS-denied, vision-based autonomy is a very popular topic in robotics right now. Most importantly: once you know where you are, how do you most efficiently navigate around the environment without bumping into things? Variations of Dijkstra’s algorithm such as A* or D* Lite can be used to quickly and efficiently calculate the optimal path over ‘nodes’, or potential waypoints. This is the same general algorithm used in google maps to find the fastest route through traffic. Putting all of this together on a flying drone took a bit of specialized hardware, some help from Robot Operating System (ROS), and a whole lot of testing. Yes, there are pre-existing packages for pretty much every feature I implemented, but where's the fun in using someone else's code? If you learned something, I’d greatly appreciate a like on this video and maybe even a subscription to my channel for more projects like this in the future.

00:00 Intro
00:56 How Waypoint Autonomy Works
03:00 Hardware Overview
04:38 Position Control Demo
06:37 Motion Planning 101
07:23 Dijkstra’s algorithm, A*, and D* Lite
09:16 Obstacle Detection
09:47 Complete Demo
12:08 Conclusions

#Drone #MotionPlanning #Autonomy

[NicholasRehm]

On a scale of “horribly underwhelming” to “ehh it’s alright, ” how did you like this project?

[iforced]

Great stuff! The forced 'long way around' test was awesome!!

[TomPittenger]

Fun Fact: ArduPilot runs Dijkstra's algorithm and another path planner in realtime. It uses a variety of inputs like multiple lidar/sonars, pre-programmed polygons (like trees and buildings), or other dynamically moving aircraft such as ADSB and/or other drones on the same network.

[ITpanda]

Autopilot drone races would be an interesting competition, maybe you can host an event? Maybe of course that has constantly changing obstacles, with a flight ceiling that would disqualify those that flew above it more than a number of times (1-3). Would bring nerdy back into drone racing, well encouraging the improvement/evolution of flight controllers.

[epicdaniel]

5:55 That's what Blue Origin said! Great video!

[TurpInTexas]

I was planning on doing something like this in my quest to build a smarter robotic mower, but you just blew my mind doing it with a drone! Lol!

[Paranalense]

Very well planned and executed, thanks for sharing. Greetings from Chile... ...and the Mythbusters poster in the end... Subscribed!

[manjunathayr]

It's pretty darn cool really really

[nt_UN_Owen]

Engineers really love to mess with stuff that can be revolutionized during their free time

[Blubbrbub]

Watching this made me remember the "Kalman filter" I heard about some time ago that allows to combine accelerator and GPS data to improve the accuracy of the "current position estimation". You could probably do something similar by having some of these tags placed at fixed known positions, so the drone can "realign" its position without relying on GPS data.

[ohitstarik]

2:30 "the drone knows where it is at all times 🧐🧐"

[lundebc]

Very nice explanation on how it works. Just getting into this topic area and will go back through this video to get more details on your implementation. I want to do something similar to my r/c lawn-mower and considering ardurover, but this approach combined with path planning/obstacle avoidance would be a very good approach.

[sang]

This blew my mind, it's truly DIY legendary. I'm new with Drone, ROS, ... I'm starting to learn this stuffs all of your projects inspired me a lot

[moisesaragon]

you are a genius, greetings from spain

[williamgillespie]

I caught a few of the Extremely subtle hints to subscribe, and did so. Thanks for the good content.

[ThereAreNoHandlesLeft]

This is so deeply nerdy and even with your excellent assistance remained over my head in a GREAT way.
Being over my head gives me something to reach for.

Great video, even more detail in the coding process would be cool. I love it.

[robmulally]

Great video, and here I was happy to have a quad running inav rth haha

[poporbit]

Great development. Thanks for sharing.

[drewskiakg]

Wow! Great video. Are you using machine learning, computer vision to recognize an object or a person?
You can make a legit drone home security system.
All you need is a wireless landing pad haha.
Can't wait for your other videos.
Thank again!

[muessliemix]

Amazing project and explanation! Keep the good work coming. 👍🏻 You earned yourself a new subscriber right there! 😉