This week we got an email from David Gómez, a research scientist at Multi-Agent Autonomous Systems Lab, Intel Labs. He and his team have done some cool work on trajectory planning in cluttered environments that we think needs to be shared. For their research they used the Crazyflie 2.0 which we think is even cooler :-). Watch the video to see how the Crazyflie 2.0 find its way though narrow corridors and obstacle dense environments.
If you are interested in the full paper, “A Hybrid Method for Online Trajectory Planning of Mobile Robots in Cluttered Environments”, you can find it under Crazyflie 2.0 publications in the research section.
This year we decided to do a short Merry Christmas video. The video was done during one chaotic evening last week were both time and technology seemed to be against us. We are anyway happy with the result which we hope will spread some Christmas joy!
PS. All flights, except the first take-off, where autonomous using the loco positioning system. Code and documentation to come later ;-). DS
Most of the time we have a few prototypes lying around that we’re working more or less on. Sometimes some of these make it into a product if we feel that they might be useful or fun for the community, like for instance the SD-card. Now it’s time for another prototype to be moved to manufacturing, a deck with VL53L0x laser ToF distance sensor.
On the Crazyflie 2.0 (and Crazyflie 1.0 10-DOF) we have a pressure sensor mounted to help control the altitude of the platform. Since air pressure is moving around a lot and the measurement is noisy it’s been very hard to get a rock-solid altitude hold working (although it’s getting closer). Already back when ST released the VL6180X we were looking at it, but the range was too short (10cm max). So when ST released the VL53L0x which has longer range (200cm max) we though this might be a good deck for the Crazyflie 2.0.
So we have a working prototype and thanks to stephanbro and Marcus Grieff we also have the firmware to use it with the Kalman filter. We are currently working at making it work together with the pressure sensor with the current altitude-hold mode.
Currently we’re working on verifying the hardware to make sure the power supply is good enough for it, but then the next step is production. Hopefully it will be available in a couple of months :-) Below is a picture of the current prototype.
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.
We attended Øredev last week and showed off our demo with an autonomous Crazyflie with a light and sound show. It was the same demo as we had in Maker Faire Berlin earlier this autumn that we wrote about last week. It is noticeable how much better the system has become since Maker Faire Berlin when it comes to performance, the Crazyflie is almost completely static when hovering in one spot now and the motions are much more snappy and exact. Hats off to the community that contributed the improvements!
At Øredev we met Ray Arkaei, the DJ that played at the party in the evening. When he realized that we used MIDI to control the position of the Crazyflie and the color of the LED-ring, he immediately offered to create his own sequence to a bit more contemporary music. This is what we love with events like Øredev, we meet people and exciting (and unexpected) events take place! He plugged in his machines and we set the goal of making a short sequence, film it and upload it to facebook. After just 10-20 minutes of experimenting (and recap from our side of how we had implemented the demo) Ray got going and soon he had had a pretty cool sequence going!
We shot this video with a phone
Arkaei shot the sequence with his 4K camera (yes, we would love to have one too!) but unfortunately did not have time finish the editing. We are eagerly awaiting the final results and will publish a link here on the blog when it is live!
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.
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.
The last couple of weeks has been really busy getting ready for the Maker Faire Berlin. The plan is to show multiple Crazyflies flying autonomously enabled by the Loco positioning system. To spice up the experience of autonomous flight and to inspire the visitors to imagine future applications we have made a small light and sound show where the Crazyflie is dancing to a soundtrack Kristoffer made.
Here is a teaser where we are maybe stretching the limits a bit too far ;-):
Taking the opportunity to exhibit what we do at events like the Maker Faire Berlin is really exciting and we are looking forward to hanging out with cool people and getting feedback about what we do.
So come and visit us at Maker Faire Berlin is Sept 30 to Oct 2 at Station Berlin. You will find us in hall 3, stand 149.
What’s better than a single Crazyflie? A swarm of them! Over a year ago our research group at the University of Southern California posted a blog post with the title “Towards CrazySwarms“, explaining how to fly six Crazyflies at the same time. Since then, we’ve expanded our fleet to 49 Crazyflies. It turns out that flying 49 requires a completely different approach. We will outline the additional challenges, and of course show a fun video!
Why is flying many Crazyflies hard? It comes down to two different categories:
Communication Limitations: The standard Crazyflie software does not support controlling more than one crazyflie per radio. Putting 49 radios on a PC is possible, but would cause very high latencies because the Universal Serial Bus (USB) operates, as the name suggests, serially in 1 ms intervals. Earlier, we showed that we can share a radio for two Crazyflies by using different addresses, but 25 radios are still too much to be handled on one PC reasonably. We can overcome this issue by reducing the amount of data to be transferred. However, this forces us to increase the autonomy of the Crazyflie. Instead of sending attitude control input for each Crazyflie at a high rate, we move the controller on-board and send high-level trajectory descriptions and external position information at a low-rate. In particular, we need to:
Move the position controller on-board, and
Be able to handle packet losses more gracefully.
i) is relatively easy, apart from the testing and tuning. For ii) we use an Extended Kalman Filter to estimate the state on-board. This state, consisting of the position, angle, and the translational velocities, is estimated by combining the on-board sensors (gyroscope, accelerometer) with external position information. Even if we are not able to send the external position for a while due to packet drops, the on-board sensors will keep the estimated state correct for a while.
Finally, we implemented broadcasts (rather than 1-to-1 communication between PC and each Crazyflie) and used a number of compression tricks in order to limit the required bandwidth further. We are able to broadcast the pose (position and rotation) for all 49 Crazyflies using just three Crazyradios 100 times per second. Each Crazyflie can handle several packet drops in a row before the state estimate becomes too unreliable to fly.
External Position Feedback: The on-board sensors of the Crazyflie are not sufficient to determine its position, so we need some external position feedback. In academia, optical motion capture systems are frequently used. They consist of a number of specialized, synchronized, high-speed infrared cameras. Each object to track is equipped with at least three retroreflective spheres (so-called markers), which reflect infrared light sent out by the IR light sources next to the cameras. If we know the pose of all cameras, we can use triangulation to determine the 3D positions of all retroreflective markers.Traditionally, motion capture systems require that each object has a unique arrangement of markers; this allows to determine each object’s position from a single frame of marker data by searching for its unique pattern. Unfortunately, the Crazyflie is too small to have 49 unique marker arrangements that can be reliably distinguished. To solve that issue, we put the Crazyflies at known positions initially and use their marker arrangement to track their position and pose over time, at 100 Hz. This allows us to use the same marker arrangement for each Crazyflie.
Putting that together (combined with an improved controller), allows us to create nice formations:
So what is next? Eventually, we will integrate our changes into the various projects (including the firmwares and the ROS driver), allowing everyone to work on and with CrazySwarms.
