We have seen a big interest in flying swarms of Crazyflies and there are many challenges in doing so. The USC ACT Lab has developed Crazyswarm, a collection of software and firmware that allows to fly big swarms of Crazyflie using a motion capture system. This project has been used by USC and other universities to fly the most impressive swarms of Crazyflie 2.0 to date.
We are very happy that we together with Wolfgang and James, the main developer of Crazyswarm, have started to merge the firmware part into the official Crazyflie firmware. Merging the code will have two great consequences: people will be able to use Crazyswarm with a Crazyflie 2.0 running the stock firmware and everybody else will be able to use functionalities that has been developed for Crazyswarm.
There is currently a couple of parts that are in the works. The state controller has been merged already. There is currently some discussion on Github on how to merge the high-level commander, a commander that would allow the Crazyflie to autonomously follow trajectories as well as other high level commands. Finally there will be some work required to adapt the Kalman filter to make it more suited to accepts measurements from a motion capture system. The Crazyflie was not developed as an autonomous platform from the beginning but it is becoming one in big part thanks to the great contributions from the community.
A great thanks to James and Wolfgang for their effort in merging CrazySwarm in the Crazyflie code-base!
Out of stock
Unfortunately we miscalculated how much China slows down during Chinese new year which has caused some products to become out of stock. One of them is the Crazyradio PA which is also causing some bundles to become out of stock as well. The good news is that the products are in transit to the warehouse and will hopefully be back in stock any day now. Until then you can use the “Item out of stock – notify me!” functionality to get notified as soon as the product is back in stock.
We just released a new version of the Bitcraze VM, version 2018.01. Nothing very new in this version, the VM has been rebuilt so that all the projects included in it are now up-to-date. This solves an issue where the Crazyflie client was blocked in the previous revision.
The current VM is running a quite old version of Ubuntu, the 14.04 LTS version. We are planning at refreshing the VM by making a new one when Ubuntu 18.04 LTS is released.
Since the Crazyflie 1 time we have been documenting the VM as a standard development environment. This has a couple of advantages:
We can distribute a fully setup development environment that has minimal dependencies with the host system
If someone has a problem with the VM, there is a bit chance we can reproduce and fix it, everyone is running the same system
Everything is pre-setup so it should be fairly quick to get started with the actual firmware or software development
However the VM solution also has drawbacks:
It requires to install and somewhat configure VirtualBox or other virtual machine software
It has some cost in performance, mostly for USB as it slows down the communication with the Crazyflie
The USB implementation seems to have bugs on Windows, which makes the communication with the Crazyflie buggy. This is currently the biggest problem!
So, the situation is not ideal, and we would love to get some feedback from the community.
There are two very different parts in the system: the lib and client in Python, and the firmwares in C.
Starting development of the python parts, on Windows/Mac/Linux, is fairly straightforward. Basically one has to install python and git, clone the projects, install dependencies and it runs. Different python IDEs can be used and work pretty much out of the box.
Starting development for the embedded C part can be a bit more challenging. On Linux and Mac it is pretty easy since it only requires to download the arm-embedded-gcc compiler and adding it to the path. On windows things are a bit more complex because you also need Make and I haven’t yet figured-out the best way to install that. Having an IDE requires to configure Eclipse CDT.
What do you think about the VM as a development environment and would you prefer other solutions like documentation for each operating system on how to install a development environment?
We have been writing a couple of times already about the new TDoA2 algorithm for the Loco Positioning System. A TDoA mode has been experimental from the day we released the LPS but we are now proud to announce that TDoA is an official positioning mode for the Loco Positioning System and the Crazyflie.
Practically it means that the Loco Positioning System now has an officially supported mode to locate and fly a swarm of Crazyflie 2.0.
We have worked these last weeks at updating documentation, the “Getting started” tutorial and releasing all the affected firmware and software. One of our goals was to make the new TDoA mode as seamless and as easy as possible to work with, this meant having everything working without having to recompile the Crazyflie or any other part of the system. The Crazyflie is now detecting the LPS mode automatically and it is possible to configure the anchors position and ranging mode remotely from the within Crazyflie client LPS tab.
If you have 8 anchors and want to convert your local positioning system to TDoA, this can be done very easily by following the new version of the getting started with loco positioning system guide.
If you want more information about the different positioning modes, we have also updated the system description.
A couple of weeks ago, I was visiting 34C3, the Chaos Communication Congress, with Fred. The trip was not ‘official’ business for Bitcraze but more of a personal interest, the Congress is a great place to be and I hope to be able to go next year. While there, we found out that Foosel was there too, she is the developer and maintainer of the Octoprint project (Our 3D printer would be much less useful without Octoprint …). It was awesome to finally meet her in real life, she has been in the Crazyflie comunity since the beginning and we have never been able to meet even though we did a couple of maker faire in Germany.
Meeting the community in person is always awesome, this is one of the best part of going to conferences.
At the end of the month we will be at FOSDEM in Belgium, Fred will be there too, he is planning to demo Crazyflie at the Eclipse booth. If anyone else is coming please let us know, we can improvise a Crazyflie meetup there.
Later in the year, in good Bitcraze style, we have not planned anything yet. Last year we went to ICRA which was a very good experience and we might be leaning for IROS this year. Let us know if there is any conference at which you would like to meet us and we will consider going.
The Loco Positioning System (LPS) default working mode is currently Two Way Ranging (TWR), it is a location mode that has the advantage of being pretty easy to implement and gives good positioning performance for most use cases and anchor setups. This was a very good reason for us to start with it. Though, TWR only supports positioning and flying of one or maybe a couple of Crazyflies, while it is not a solution to fly a swarm.
One solution to fly a swarm is an algorithm called Time Difference of Arrival (TDoA). We have had a prototype implementation for a while but we experienced problems with outliers, most of them where due to the fact that we where loosing a lot of packets and thus using bad data.
To solve these issues, TDoA2 makes two changes:
Each packet has a sequence number and each timestamps is associated with the sequence number of the packet it has been created from
The distances between anchors are calculated and transmitted by the anchors
A slightly simplified explanation follows to outline why this helps (a more detailed explanation of how TDoA works is available in the wiki).
We start by assuming that all timestamps are available to the tag, this is done by transmitting them in the packets from the anchors to the copter.
The end goal is to calculate the difference of time of arrival between two packets from two different anchors. Assuming we have the transmission time of the packets in the same clock, all we need to do is to subtract the time between the two transmissions with the time between the two receptions:
0 – anchor 0, 1 – anchor 1, T – Tag (that is the LPS deck on the Crazyflie)
To do so we need to have the time it took for the packet to travel between the two anchors, this will enable us to calculate the transmit time of P2 in anchor 1, this can be done by calculating the TWR time of flight between the two anchors, this would require the tag to receive 3 packets in sequence:
So now for the part where TDoA2 helps: previously we had to have the 3 packets in sequence in order to calculate a TDoA, if any one of these where missing the measurement would fail or worse, it could give the wrong result. Since we did not have sequence numbers, it was hard to detect packet loss. Now that we have sequence numbers, we can understand when a packet is missing and discard the faulty data. We also do not have to calculate the distance between anchors in the tag anymore, it is calculated by the anchors themselves. This means that we can calculate a TDoA with only two consecutive packets which increases the probability of a successful calculation substantially.
To reduce packet loss even more, we have also added functionality to automatically reduce the transmission power of the NRF radio (the one talking to the Crazyradio dongle) when the LPS deck is detected. It has turned out that the NRF radio transmissions are interfering with UWB radio reception, and since most indoor use cases does not require full output power we figured that this was a good trade-off.
The results we have seen with the new protocol is quite impressive: TDoA is usually very sensitive to the tag being inside the convex hull, so much so that with the first TDoA protocol we had to start the Crazyflie from about 30cm up to be well within the convex hull. This is not required anymore and the position is still good enough to fly even a bit outside of the convex hull. The outliers are also greatly reduced which makes this new TDoA mode behave very close to the current TWR mode, but with the capability to locate as many Crazyflies as you want:
Added to that, we have also implemented anchor position handling in the TDoA2 protocol and this means that it is now as easy to setup a system with TDoA2 as with TWR:
We are now working on finishing the last functionality, like switching between algorithms (TWR and TDoA) and on writing a “getting started guide”. When that is done TDoA will become an official mode for the LPS.
In the mean time, if you are adventurous, you can try it yourself. It has been pushed in the master branch of the Crazyflie firmware and the LPS node firmware. You should re-flash the Crazyflie firmware, both STM32 and nRF51, from master and the anchors from master too.
It has been a while since we have made a blog post about the the community and quite a lot has happened, and is about to happen, so we though we would do an update for this Monday post.
Fred, the Crazyflie android client community maintainer was visiting us last week. He is making great progress on the Java Crazyflie lib that is going to be used in the Android client as well as in PC clients. The lib is still experimental but when finished it will allow to connect and use a Crazyflie from any Java program, there has already been some successful experimentation done using it from Processing.
Thanks to Sean Kelly, the Crazyflie 2.0 is now officially supported by the Betaflight flight controller firmware. Betaflight is a flight controller firmware used a lot in the FPV and drone racing community. This is the announcement by theseankelly in the forum:
Betaflight 3.2 was officially released this month. This is the first release that contains the Crazyflie 2.0 target by default, so you don’t need to clone and build from source anymore. It’s available as a target in the betaflight configurator from the google chrome store! I’ve tested it out and it works as expected. Haven’t tested the BigQuad variant, but that’s also available in the app by default.
The Crazyswarm project, by Wolfgang Hoenig and James A. Preiss from USC ACTlab has been presented at ICRA 2017. It is a framework that allows to fly swarms of Crazyflie 2.0 using a motion capture system. There is currently some work done on merging the Crazyswarm project into the Crazyflie master branch, this will make it even easier to fly a swarm of Crazyflie. In the meantime the project is well documented and can be used by anyone that has a couple of Crazyflies and a motion capture system.
The idea is that we can detect the proximity of the hand with the ranging sensor contained in the flow breakout and detect how the hand is moving with the optical flow sensor. The flow sensor is very similar to an optical mouse sensor so we are just inverting the concept to move the environment (the hand) instead of moving the flow sensor against a table. Using an Arduino Leonardo our hack is recognized as a regular mouse by any computer.
As a result, it works quite well but it requires some training to get the mouse to go where we want. We would not use this as our regular pointing device any time soon but we think is a nice example of what can be achieved with the flow breakout board:
The Flow breakout board is built around the Pixart PMW3901 optical flow tracking sensor and the ST VL53L0x ranging sensor and measures motion in 3 dimensions. We have used the same sensors in the Flow deck which is used by the Crazyflie drone for autonomous flight, but we thought that the functionality is so awesome that we developed the Flow breakout and made it compatible with Arduino to make it easy to use. With the Flow breakout it is possible create applications such as motion tracking of a robot, counting people entering a room or gesture tracking.
When you get your Flow breakout, follow the getting started guide to quickly get up and going by hooking it up to an Arduino and measure motion.
In the following weeks we are going to make a couple of Hackster project around the Flow breakout board so stay tuned for more motion tracking!
The Crazyflie, the original one, usually called Crazyflie 1 to avoid confusion, was the first commercially available open source nano quadcopter back in 2013. After getting feedback on the platform and having a lot of ideas of things that could be improved, we developed the Crazyflie 2.0 during 2014 and released the same fall. We decided we wanted to keep full backward compatibility with Crazyflie 1, both in the firmware project and in the different clients and support libraries even though we now had more processing power and RAM.
But during the last year we’ve almost exclusively been adding functionality that is Crazyflie 2.0 specific, while still trying to stay inside the constraints of the Crazyflie 1. We’ve also seen a decline in the discussions and interest of the Crazyflie 1. So this week when we once again broke the build because we run out of RAM in the Crazyflie 1, we decided to remove the Crazyflie 1 support from the Crazyflie firmware project. It’s of course with a heavy heart we do this, but we feel that in order for the Crazyflie 2.0 to move forward it’s a must. The last release that’s compatible with the Crazyflie 1 is 2017.6.
But if you’re still using the Crazyflie 1, don’t worry we’re not completely dropping it, we will continue to carry spare parts and if anyone wants to continue firmware development we will be happy to assist. If anyone is motivated, the code can be branched from the last release and we could make a new repository to host the Crazyflie 1 code.
Last week we released the Flow deck, it enables you to get really stable autonomous flight with the Crazyflie without requiring an external positioning system. We have been lucky to get access to the brand new Pixart PMW3901 optical flow sensor, the core of the Flow deck, very early and we wanted to bring this awesome functionality to everyone, including those without a Crazyflie. The solution is the Flow breakout board, it enables anyone to use this new optical flow sensor for any kind of motion tracking.
The flow breakout contains a PMW3901 optical flow sensor and a VL53L0x time of flight ranging sensor, the same sensors that are mounted on the flow deck. We have also added voltage translation logic that allows you to use the flow breakout with a system voltage of 3 to 5V that makes it possible to use it directly with any Arduino board and most embedded system. Further more we have written an Arduino driver for the PMW3901 optical flow sensor to make it easy to use the breakout deck. For the VL53L0x there are already a couple of drivers available out there.
The flow breakout is currently being manufactured and will be available in our shop in a couple of weeks. If you want to be notified of the Flow breakout board availability, please sign up in the shop or follow us on twitter.
