For the third year we will be at FOSDEM on Saturday 4 and Sunday 5 February 2017 in Brussels. The last two years we have been present and Fred, the Android client maintainer, has had a lightning talk about the Crazyflie.
If you are planing at being at FOSDEM and want to meet with us just tell us in the comment, we would be really happy to meet Crazyflie users. There will be almost all of the Bitcraze team and we will have Crazyflie and a Loco Positioning System so it might even be possible to do some flight or demo on the side.
At FOSDEM 2016 we met someone from Bosch Sensortec, he was very interested by the Crazyflie and got one. Apparently his college liked the Crazyflie too because soon later we where contacted by Bosch that wanted to make a deck for the Crazyflie containing a brunch of there sensor. We have been tweeting about this board before and now we just pushed the drivers for some of the sensors into the Crazyflie main branch.
The deck has an impressive list of sensor onboard:
BMI055: 6 Axis gyro and accelerometer, with closed loop technology gyroscope
Thats a lot of data, and there is also an non-populated footprint for a BMF055 which is a BMI055 and an Atmel ARM Cortex-M0 in the same package, this is something that could be very interesting to play with in the future. The drivers and the integration are still in early stage but what has been pushed so far is support for the BMI055 and BMI160. We look forward to tuning those sensors and testing the others as well!
Bosch has made most of the work with this deck them selves and we have provided mainly guidance and support, a big benefit of open source! That has been working great and it has been very fun working with them. We are not sure if this is going to be part of a product yet, as in releasing a deck full of sensors. Please tell us what you think and if anyone would have use for such deck.
Last week we reached a milestone for our Loco Positioning System: we got 5 Crazyflie 2.0 to fly in a swarm with Time Difference of Arrival measurements. This is a great step closer to making the LPS leave the early-access state.
Until now, positioning has been done using a method called Two Way Ranging (TWR). The advantage of TWR ranging is that it allows us to easily get ranges to the anchors by actively pinging them in sequence. Based on these ranges we can then calculate the current Crazyflie position and control the Crazyflie to move to a wanted position. The big drawback though is that since each Crazyflie has to actively transmit packets to ping anchors, flying many Crazyflie means sharing the air and so the more we want to fly the less ranging each Crazyflie can do. In other words: it does not scale.
TDoA measurement consist of measuring the difference of flight time between packets coming from different anchors and this is harder to achieve since the anchor clocks must be synchronized to each other. The killer feature of TDoA is that it can be implemented using unidirectional packet sent from the anchor system and received by the tag/Crazyflie. It means that as soon as you get one Crazyflie flying with TDoA, you can get as many as you want since the Crazyflies do not have to transmit anything.
This is what happened last week: on Thursday evening we got 1 Crazyflie to fly with TDoA measurements. On Friday we tried 3 and then 5 without much effort. It was just matter of modifying the ROS launchfile to connect more crazyflies, a copy-paste operation.
There still seems to be a margin for progression to get even more stable flight with TDoA and we are also working on making the LPS and Swarm work with our Python client which will make it easier to use outside a robotic lab.
If you want to try the (very experimental!) TDoA mode with your loco positioning system we have documented how to get it to work on the wiki.
Thanks a lot to the growing community that is supporting us and allow us to move faster towards a Crazyflie swarm.
Loco positioning system is still in Early access which means that things are moving fast. Since the release of the loco positioning system a Kalman filter has been contributed by Mike Hammer at ETH Zurich. The Kalman filter allows to calculate the position estimate in the Crazyflie and merges the Loco positioning system information with internal sensor to generate a much better estimate. We also worked on improving the anchor firmware, it is now ranging faster and we fixed a bug that was making the anchor hang sometime. Finally stephanbro on github pushed an improved position controller that improved the stability of flight a lot.
Because of all these changes we have decided to make a new video and to rewrite the documentation on the wiki a bit. Enjoy!
On the development side, we have extended the Loco Positioning system to position 2 concurrent Tags by using TDMA (Time Division Multiple Access) where each Tag is allocated a time slot to use to range to the anchors.
This works fine for a few Tags, but does not scale very well for a larger numbers of tags. If you want to experiment by yourself there is some instruction in the git commit. Be aware that this is still experimental enough for us to break it without warning so keep track of the git commits when you pull the latest version of the firmware. Currently we are working on a TDoA (Time Difference Of Arrival) mode that will scale to concurrently position virtually an infinite number of tags, hopefully you will soon be able to see commits on that on our Github projects.
We have always been interested in controlling Crazyflie with various devices. For example we had the Leap Motion that enabled us to control the Crazyflie with our bare hand. Then we hacked a glove for Arduino day. At Maker faire Berlin 2016 we met the team from Specktr. Specktr is a midi glove and since our demo was controlled with midi we had to try connecting the Specktr with Crazyfile 2.0 flying using Loco Positioning System!
We met in the evening, after the faire was closed, and started hacking to map the midi messages transmitted by the glove to our midi to position ROS node. After a couple of mandatory crashes and crazy behavior (like setting the flight area way too big and sending the Crazyflie high speed away at the snap of a finger, too bad we have no video of that …) we had things working well and the glove could control the Crazyflie X position:
The second and last day of the faire we did a more proper connection where both X and Y could be controlled. The result is quite nice. It looks near magic, and quite fun, to control Crazyflie just by just moving the hand:
Speccktr is currently running a crowd funding campaign and we cannot wait to get ours to be able to hack more with it together with Crazyflie and Loco Positioning System.
One week ago we where presenting Crazyflie 2.0 and the Loco Positioning System at Maker Faire Berlin 2016. It was a lot of fun being there, we enjoyed it very much, and it also required a couple of weeks of preparation. The preparation was both mechanical and markerting: out booth was built with and outdoor tent frame and we featured the first roll-ups of Bitcraze history (almost felt a bit too ‘corporate’ for us :-).
On the technical side it was an opportunity to test Crazyflie and the Loco Positioning System in real event situation. This required stabilizing the system and testing it so that no bad surprises would happen during the faire. The result is pretty good: we flew more than 91% of the opening time, we had 2 fly-away the first day, fixed the problem and had none the second day. We were flying with 2 Crazyflie sequentially and had not broken any motor mount or other part during opening hours (some crazyness did happen after-hours though, maybe more on that on a later post ;-).
For our demo the Crazyflie was flying autonomously with the loco positioning system using the Kalman filter to fly towards a given x/y/z set-point. We made a midi-to-crazyflie bridge in ROS that allowed to give control of the Crazyflie position via a midi cable. We actually used a physical midi cable which was the safest and simplest. On the other side of the midi cable was a computer running a midi sequencer, lmms. Part of the sequence was playing actual music to make the Crazyflie dance and part was just silent movement. The setup looked like that:
Midi can encode notes pitch (ie. where in the piano you play) and velocity (ie. how hard you press the piano key). The midi track contained 4 tracks: X, Y, Z and LED-ring. In X, Y, Z tracks the note pitch converted into a position and we don’t use the velocity. The led ring track maps the note pitch to a color and the velocity to a brightness. It looks like that:
This setup was a bit of a test, we found it to be very reliable. Some functionality were implemented on-site after Friday morning experience: automatic landing when the battery was low and reconnect on take-off to allow taking off without restarting anything in the PC just at a press of a button. The midi link worked well even though it feels a bit hackish to setup a choreography like that. If you have any better idea what to use to make a Crazyflie dance please tell us!
Last but not the least we have share all the codes, files and documentation for this demo on github so that you can run it yourself with an loco positioning system. We also made a short video showing the demo in action:
We are just back from the Maker Faire Berlin where we have met lot of interesting people and shown the loco positioning system. We have calculated that Crazyflie 2.0 has flown for more than 91% of the faire thanks to the autonomous flight with Loco Positioning System.
Our neighbor at the Maker Faire was Gerhard Fließ from Deskbreeze and he was presenting a mini desktop wind-tunnel:
This was a great opportunity for us to test the Crazyflie in a wind-tunel. The result is really impressive slow motion videos:
The wind-tunnel is mainly designed for education. The wind goes at 1 m/s which is apparently too slow for aerodynamic study but nevertheless we can see some interesting effects. Then the propeller pulls the air, we can see the lines getting tighter just before the propeller, this is a sign of higher speed flow and lower pressure. The difference of pressure between the bottom and the top of the propeller is what makes the Crazyflie fly. When the Crazyflie pushes the airflow, simulating a descent, we can see an oscillation of the air flow. This is most likely what can cause instability when descending fast.
We will post more about the Maker Faire Berlin and our autonomous flight demo in the following weeks so stay tuned. Thanks to all we have met, it is awesome to meet and talk about the Crazyflie in person. A mostly great thanks to Fredg (derf on the forum ;), that was there to help us during the whole week end.
Until now, the Loco Positioning System have been limited to flying only one Crazyflie autonomously. In this post we will try to explain the reason of this limitation and what are the way forward.
The loco positioning system is based on Ultra Wide Band (UWB) radios that can very precisely measure the time of departure and arrival of a radio packet. This allows us to do two things:
Use these times directly to calculate the flight time of the radio packet. This is called time of arrival (ToA) measurement, it can be done by simply pinging one anchor. No extra synchronization is required.
Use the difference between the arrival of packets from two different anchors. This is called time difference of arrival (TDoA), it requires the system of anchors to be synchronized together.
The method 1) is simpler to implement since it does not require the anchor system to be synchronized, though it requires bidirectional communication between the tag (eg. Crazyflie) we want to locate and the anchors. It means that if you want to locate more than one tag you have to somehow share the air by not ranging all at the same time. The method 2) requires extra work to synchronize the system of anchor and is theoretically more sensitive to measurement noise. However TDoA measurements have a huge advantage: they can be made to work with unidirectional signal sent from the anchors. This means that the tag only has to listen to the air to receive all information needed to locate itself. This allows to scale the location system to as many tag as we want since adding a tag do not have to share the air, they are not transmitting anything.
So far we have been concentrating on ToA measurement since it could easily be implemented and gives us the best theoretical ranging performance. This allows to develop the algorithms to calculate position estimates and stabilize the autonomous flight. The problem is that, since we are just ranging as fast as possible with all the anchors of the system, one Crazyflie will take all the available air-time and we cannot fly another Crazyflie at the same time. We have just implemented a solution to fly more than one Crazyflie with ToA measurement using time-slots, this is called TDMA for Time Division Multiple Access, and it can be done without anchor code modification. We are working on the Maker Faire demo using this method and it is starting to work quite well:
For TDMA we define frame and time slot. One time slot is a space in time where one tag will be allowed to communicate without risking collision with others. One frame is a group of timeslot. Each Crazyflie is configured to use one time slot in each frame.
TDMA frame structure. Image from the Wikipedia TDMA article.
Normally implementing TDMA would require some kind of synchronization to make sure each Crazyflie knows when its time slot starts. With the LPS we are in luck though since transmitting time is part of the way the ranging is working: we do not have to implement new messages or even to modify the anchors to implement TDMA.
We chose the timer in anchor 1 as our master clock for TDMA. When a Crazyflie starts it ranges with anchor 1 which allows to get the current time in anchor 1, then the start of the next frame can be calculated and the Crazyflie can schedule to range in its next time slot. We range with one anchor per time slot and each time we range with anchor 1 we get a chance to re-synchronize.
The TDMA has been pushed to the Crazyflie master branch. It is documented in the commit message so please feel free to test it, report, and pull-request ;-). We have tested running in 2 slots mode with success. Very quickly though, when adding more time slots, the performance deteriorates because the rate of ranging per Crazyflie decreases. Then TDoA will lead to better performance which is the next target, after the Maker Faire Berlin :-).
As noted in a previous post, Mike Hamer from ETH Zurich has been implementing an Extended Kalman Filter (EKF) for the Crazyflie. The beginning of this week I am visiting Michael at ETH and we have now pushed the EKF to the Crazyflie master branch!
Visiting ETH is really nice, and it is very impressive to see the Flying Machine Arena in real life. Though, owing to the Crazyflie’s size, we do not need such a big space and can work in a more regular-sized room.
The EKF has now been added to the master branch but is not enabled by default. It is currently intended to be used with the Loco positioning system (although it should be easy enough to integrate with onboard GPS, or potentially offboard motion capture measurements). While it does fly better than the currently used, offboard particle filter for autonomous flight, it requires some care to work properly. I am going to update the wiki description for the loco positioning to document how to get started with the EKF during the week. Our hope is that through community engagement and feedback, we can continue to improve and tune the filter, now that Mike has put the basic functionality in place.
The greatest enhancement is that the Crazyflie is now able to estimate its own position, without the help of an external computer. Coupled with the onboard controller, the Crazyflie can now fly fully autonomously. I have also pushed a new example in the Crazyflie python lib that shows how to send an X/Y/Z set-point to fly the Crazyflie, allowing it to fly through waypoints.
In the near future we (Bitcraze, and hopefully, the community!) need to work on a couple of more things to make it fly even better
Revamp of the controller: the current controller is a position controller, splitting it in two controllers, one for position and one for velocity, would allow for a more stable flight and to finally use TheSeanKelly new PID settings!
Implementing TDOA positioning on the LPS would allow more than one Crazyflie to fly at the same time
Implementing the new commander packet in the Crazyflie, python lib and ROS driver. This will allow us to stop hacking the current commander each time we need a new functionality (such as onboard position control) — and since I have push rights, only my hacks get pushed, which is unfair ;-).
Mike will describe the Kalman filter in greater details in a future post. In the mean time we will update on the progress in the Loco Positioning mailing list.
The loco positioning hardware is now manufactured and we are working hard on making it available. Loco positioning is still in early access, which means that we have tested the hardware but that the software still requires some love.
One of the big features still to implement is a position stabilization and position sensor fusion in the Crazyflie. This has been worked on from two fronts in the last weeks.
Community member jackemoore has been working hard on getting the Crazyflie 2.0 with a GPS deck working with position hold. He is getting close to having a GPS position hold working but has stumbled upon some system bugs that have to be solved first. You can follow, or even better help out, with the development on the forum post.
Crazyflie 2.0 with GPS deck
GPS location in the Crazyflie client
Mike Hamer, from ETH Zurich, has started to implement a Kalman filter, based on one of his publications, for the Crazyflie 2.0 firmware. This is still very much a work in progress but the initial results look promising. Mike has found and fixed a bunch of bugs on the way, which has greatly improved the firmware quality and stability. Since it is able to fuse the position estimate with the internal sensors, the Kalman filter will pair nicely with the GPS implementation from jackemoore to add a new layer of stability, as well as with the Loco positioning system. In addition, the Kalman filter is being written in such a way that it should be easy to incorporate additional sensors into the estimate. Keep your eyes open for a blog post in a couple of weeks with more detail on the Kalman filter’s inner workings, and hopefully a fully functional Kalman filter in the Crazyflie shortly thereafter :-).
