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.

As we announced recently, the Flow deck for the Crazyflie has been released. There was a high demand the first days and we were unfortunately out of stock in the store for a short time, but now we are restocked and the deck is available again. We also got a shipment of a few production Flow decks to the office, and of course we wanted to play a bit with them to find the limits. During development of the deck we only had one or two working prototypes at a time, but now there were manny, so what could we do?

Swarm with the Flow deck

Aggressive flying

So far we have flown slowish when using the Flow deck and we know that works, but what about more aggressive manoeuvres? We modified the flowsequenceSync.py script in the examples directory of the crazyflie-lib-python library. The original script flies a figure 8 at 0.5 m/s, and we spiced it up to do 1.5 m/s instead.

Link to video

It works pretty well as you can see in the video but we get a drift for every finished figure 8 and we have not really figured out yet the origin of this error. There are a number of potential error sources but it needs further investigation to be fully understod.

Flying one Crazyflie above another

What if one Crazyflie flies above another? How will that affect the performance of the Flow deck? The optical flow sensor is in essence a camera detecting the motion of the floor, a Crazyflie passing through the field of view could potentially confuse the system.

We set up two Crazyflies to fly on a straight line in opposite directions, one 0.5 m above the other. The result was that the top Crazyflie was almost not affected at all when the other passed under it, just a small jerk. The lower one on the other hand, passed through the turbulence of the top one and this caused it to swing quite a lot, though it managed to more or less continued in the correct direction it was decidedly out of track. As expected, flying above another Crazyflie is not a good idea, at least not too close.

Flying a swarm with the Flow deck

When flying with the Flow deck all navigation is based on dead reckoning from the starting position, is it possible to fly a swarm using this technique? We thought that by putting the Crazyflies in well known starting positions/orientations and feed them trajectories that do not cross (or pass over each other) it should be possible. The start turned out to be critical as the system is a bit shaky at altitudes under 10 cm when the sensors on the Flow deck are not working very well yet. Sometimes the Crazyflie moves slightly during take-off and this can be a showstopper if it rotates a bit for instance, as the trajectory also will be rotated. It worked pretty well in most cases but sometimes a restart was required.

We were inspired by the Crazyswarm from USC and decided to fly 5 Crazyflies with one in the center and the other 4 spinning around it. Note the center Crazyflie turning but staying on the spot. 

Link to video

We used the Swarm class in the python library to control the 5 Crazyflies. The code used to connect to the Crazyflies one by one which takes quite some time, we changed it to a parallel connect while we were at it and got a significant speed up.

The code for the swarm is available as an example in the python library.

It is a lot of fun playing with the Flow deck and scripting flights. I know it might be silly, but we laugh the hardest when we fail and crash, the more spectacular the crash the more happiness!

The Flow breakout

For other robotics projects that don’t use the Crazyflie, remember that the same functionality as the Flow deck delivers soon will be available in the Flow breakout board. It is compatible with Arduino and other hosts.

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.

We have had an implementation of a Time Difference of Arrival algorithm (TDoA) in the Crazyflie 2.o and the Loco Positioning System for quite a long time. The coolest feature of the TDoA algorithm is that it can be used to position virtually unlimited number of Crazyflies concurrently as opposed to the standard Two Way Ranging algorithm that is limited to one (or very few Crazyflies). The original implementation is working pretty well but contains some flaws that we are not completely happy with, hence we have not released it officially and are still calling it experimental. Since support for tracking multiple objects is a requirement for flying swarms and we like swarms, we have started to iron out the problems. 

In the current implementation each anchor transmits the time of the transmission and the times of the latest reception of transmissions from all other anchors about every 16 ms. From this information it is possible to calculate the difference in time of flight for the radio waves from two anchors to the Crazyflie. When we know the difference in time of arrival, by multiplying with the speed of light we get the difference in distance and can calculate the position of the Crazyflie. This all sounds fine and dandy but the set up has some problems, the biggest one being error handling. If one or more packets are lost, either from anchor to Crazyflie or anchor to anchor, there is no deterministic way to detect it in some cases. The current algorithm relies on sanity checking the calculated result and discarding data that looks suspicious, which is usually easy as the distances quickly gets unrealistic (several thousands of meters!). We suspect that some erroneous values slip through the check though and we would like to be able to really understand when data is valid or not.

TDoA 2.0

What we are working on now is to add a sequence numbering scheme to enable the receiving party to understand when a packet has been lost. With this information it will be possible to discard bad data as well as use the available information better. While we are re-writing the code we are also moving a part of the algorithm from the Crazyflie to the anchors, after all there is a CPU in the anchors that is not fully utilized. The idea is to let each anchor continuously calculate the distance to all other anchors and add this information to the messages it transmits, which will reduce the work in the Crazyflie.

This is work in progress and we are not completely sure where we will end up, but we are aiming at making the TDoA mode part of the official release at some point.

Sensor fusion

Related to the Loco Positioning system is our line of other positioning sensors; the Z-ranger deck and the Flow deck. The Flow deck has really good precision at low altitudes but can not provide absolute positioning while the Loco Positioning system does not have the same precision but absolute position capabilities. So what if we fuse the information from the Flow deck with the Loco Positioning system? We have tried it out and it works pretty well, we can get the best of two worlds! The Z-ranger can also be used in the same way to improve the Z component of the estimated position when flying bellow ~1m.

Even though it works using multiple positioning sensors at the same time, there is room for improvements and some tweaking will be required to make it rock solid.

At any given time we have a bunch of deck ideas floating around. Some of them might not be doable (or very hard), but still fun to discuss. Other we just never get around to since we’re always pressed for time. The “obstacle avoidance” deck is one of the latter ones.

The idea with the “obstacle avoidance” deck (current working name in lack of imagination) is to mount one of the VL53L0x ToF distance sensors, the same we have on the Z-ranger and the Flow deck, in each direction. This would allow you to keep a distance to the ground, avoid the walls (or any other obstacles you might fly into) and also keep away from the ceiling. Basically you could do a “turtle bot” that just flies around randomly without crashing. Another fun idea we’ve been discussing is being able to SLAM the room you’re flying in. If you can keep track of how you are moving around (with the Flow deck, Loco positioning system or any other means) while you’re measuring the distance on all sides you could make a map of the room.

After discussing this on and off for a some time, mainly focusing on mechanical and production issues of the design, we decided to just try out the concept with a simple prototype. The prototype, named “OA”, has daughter boards with VL53L0x sensors mounted front/back, left/right as well as one sensor facing up. It’s designed to be mounted on the top of the Crazyflie 2.0 and combined with the Flow deck which will give relative movement and also the sixth direction, distance to the floor. One of the issues with the design is that all the VL53L0x sensors are on the same I2C bus with the same address. To work around this the sensor has a nifty feature where you can re-program the I2C address. For this to work you need to release the reset of the sensors one by one: release the first reset, reprogram the address and then release the reset of the next sensor. The reset for the VL53L0x is not cabled on the Flow deck, so this is the first to be re-programmed. Then the reset will be released one-by-one for the sensors on the OA deck. In order to control the reset pins on the deck there’s a 8bit I2C GPIO expander. The reason for the GPIO expander is to use as few GPIOs on the deck connector as possible to keep the compatibility with other decks high. For instance the deck will work fine with the Loco positioning deck.

The goal with the prototype is to try out the concept of the deck and to see if it’s feasible. A few of the things we need to sort out is:

• Mechanical solution for side senors (front, back, left and right)
• Interference between sensors
• Update rate when we have 6 sensors on the same bus which we might have to run one-by-one to avoid interference

The current status is that we’ve verified the electronics and written the I2C GPIO expander drivers to test all the sensors. The next step is to work on a new VL53L0x driver to allow multiple sensors running at the same time, which will force some refactoring of the firmware.  Once we’ve made some more progress we’ll do another post and report the results. If you have any feedback on the design/concept or have any ideas of what the deck could be useful for, don’t hesitate to drop a comment below.

It was inevitable. At some point we needed to do a drone show of our own and wouldn’t the best occasion be on one of our coworkers wedding party! Well we have done demos before on maker fairs and conferences but never a one time show. This time we also had the possibility to collaborate with an acrobat, namely Arnauds brother, Adrien. Perfect match! The only problem was that we only had one day to pull something off and no possibility to rehearse anything with Adrien before the live show. Probably a piece of cake for a true artist such as Adrien but for newbies like us it was definitely increasing the stakes. There was no time to wank about that but better to get our hands dirty.

We wanted to create a choreography with a Crazyflie interacting with Adrien as he did some awesome acrobatics. The Crayzflie should be clearly visible with lights and we wanted it all to be synchronized to music. The final requirement was to minimize the equipment required since the wedding was abroad and we did not want to carry too much equipment.

We decided to use the Loco positioning system as a base to be able to do scripted flight and chose Two Way Ranging to reduce the number of anchors needed. We used only four anchors arranged as a 3×3 m square, three of them on the floor and the fourth 1.5 meters up on a tripod. Two Way Ranging works very well outside of the convex hull (which is really small in this case) but with the drawback that we only could position one Crazyflie – no swarm show.
For the visibility we used a prototype deck with a high intensity LED pointing downwards.

Photo by Eric Cunha

Again to minimize the equipment we decided to pre-program the sequence in the Crazyflie and put a start button on it to run the sequence. The piece of music to be used (composed by the groom during the bachelor party) was about one and a half minute long and the idea was to start the music and the sequence manually at exactly the same time and let them run without any further synchronisation.

We based our purpose built firmware on the demo code from ICRA earlier this year. It contained the sequencing but we had to add functionality to control the LED. We wrote a python script that generated data for the sequence that could be pasted into the firmware. A button was soldered on top of the Loco Positioning Deck and connected to a GPIO pin to be used as a start button.

We are engineers and not choreographers but after some trial and error we managed to create a sequence with light that was synchronized to the music. The overall idea was to start the Crazyflie on the floor in the center of the space, go out into the audience during the intro and turn on the light over Adrian (that was carefully positioned on the correct spot) and guide him onto the “stage”. While Adrien improvised acrobatics on the floor the Crazyflie circled around and above him with flashing lights. At the end of the music the procedure was reversed and the Crazyflie guided him back into the crowd and landed quietly in the center of the stage.

Photo by Eric Cunha

After dinner when it was time for the show we set up the positioning system and the crowd gathered. The first two attempts failed as it turned out that the ceiling of the venue was lower than expected and the Crazyflie hit a beam! What to do? We had a pre-programmed sequence that was going too high! We simply moved the anchors 30 cm away from each other and “stretched” the space to trick the Positioning system a bit. We had not tried this before and live hacking is a bit stressful, but we were possibly strengthened by one or two glasses of wine

The third attempt was almost perfect with an incredible performance by Adrien! Phhuuu and what a success on the third attempt. Heart failure was close but did not kill us this time! Maybe this is why we stay away from live shows and rather sitt down in a dark basement coding :-).

A long time ago we got a request for a bright LED deck from a community member. When working with high powered leds heat becomes a problem that needs to be taken into account. From the community member we got suggestions of using one of the luxeon rebel leds and so we did. We designed a prototype pretty quickly but also realized that it is a bit harder than we first thought. If using a simple control scheme such as PWM and a mosfet the circuit is simple but brightness will be effected by battery voltage. Using a dedicated LED driver the brightness would be stable but the circuit more complicated and expensive. Trying to list the pros and cons:

MOSFET
+ Low complexity
+ Low cost
+ High efficiency
– varying brightness depending on battery voltage
– Might stress LED (could be solved with low ohm resistor)

LED driver
+ Stable brightness
+ Not as high efficiency (~80%)
– Higher cost
– Higher complexity

We ended up trying booth. The LED driver design failed due to that the battery voltage needed to be lower than the LED voltage + schottky and it is just in the middle. The PWM design half failed since the LED anode and cathode was swapped in the design but was possible to patch afterward. So at least we got something up and running.

The effect is very nice and it is what we used for the wedding show. The question now is, is this something we should finish and put in the store?

A few weeks ago we wrote about a new prototype that we call “the obstacle avoidance deck”. Basically it’s a deck fitted with multiple VL53L0x ToF distance sensors that measures the distance front/back, right/left and up of the Crazyflie 2.0. Combined with the Flow deck this gives you an X/Y/Z robot that you can program fly around avoiding obstacles which doesn’t need any external positioning system.

After implementing firmware support for the deck (see #253 and #254) we’ve finally had a chance to do some initial testing, see the video below. In the current implementation we’re doing the measurements in the firmware but using the logging framework to get all the distances into a Python script which does the movement control. Since we have the Flow deck attached we can control the Crazyflie 2.0 in velocity mode, which means we can say things like “Go forward with 0.5 m/s until the forward sensor shows a distance lower than 50cm” or “Go forward 1 m/s for 1s and rotate to measure the distance to all objects”. Since there’s no real-time requirements we can move the complexity of the algorithm from the firmware into external scripting which makes it a lot easier to develop. Now we’re really eager to start setting up obstacle courses and time how fast we can move though them

The results from the testing shows that our two main concerns aren’t an issue: The sensors doesn’t seem to interfere with each other and we can sample them all at high-enough frequency without occupying the bus too heavily (currently we’re doing 20Hz). The next step is figuring out the requirements (i.e how many VL53L0x sensors are needed, do we really need the back one?) and a mechanical solution for attaching the sensors in production. If there’s any feedback let us know now and we’ll try to get it into the design. Also, we really need a new name for the board. Any suggestions?

One of the pain points when setting up the Loco Positioning system is to measure the anchor positions and enter them into the system. I wanted to see if I could automate this task and let the system calculate the positions, and if so understand what kind of precision to expect. I have spent a few Fun Fridays playing with this problem and this is what I have found so far.

The problem can be broken down into two parts:
1. How to calculate the anchor positions. What data is required?
2. How to define the coordinate system. To make it useful the user must to be able to define the coordinate system in a simple way.

How to calculate the anchor positions

The general idea of how to calculate the anchor positions is to set up a system of equations describing the distances between the anchors and/or the Crayzflie and solve for the anchor positions. The equations will be non linear and the (possibly naive) plan is to use the Gauss Newton method to solve the system.

To understand how to calculate the anchor positions we must first take a look at the data that is available. The Loco Positioning system can be run in two different modes: Two Way ranging (default mode) and TDoA.

Two way ranging

In the Two Way ranging mode we measure the distance between each anchor and the Crazyflie and to get enough data we must record ranging data for multiple positions. The anchor positions are unknown, and for each new Crazyflie position we add yet a new unknown position, on the other hand we measure the ranges to the anchors so these are knowns. 

The equations used are simply to calculate the distance between the assumed position of each anchor and the Crazyflie and then subtracting it from the measured distance.

TDoA

In TDoA we measure the Time Difference of Arrival, that is the difference in distance to two anchors from the Crazyflie’s position. It is probably possible to use this information, but I was looking for a different solution here. In our new TDoA implementation that we have been playing with a bit, we get the distance between all anchors (calculated in the anchors) as a side effect. 

In this case the Crazflie is not really needed and the equations describe the distance between assumed anchor positions versus measured distances.

How to define the coordinate system

To get a useable positioning system, the coordinate system must be well defined and oriented in a practical direction. For example when writing a script you probably want (0, 0, 0) to be at some specific spot, the X-axis pointing in a certain direction, the Z-axis to point up and so on. My initial idea was to use the anchors to define the coordinate system, use anchor 0 as (0, 0, 0), let the X-axis pass through anchor 1 and so on. Just by looking at our flight lab I realised that this would be too limiting and decided that the coordinate system should be completely disconnected from the anchor positions, but still easy to define. I also realised that a really good way to tell the system about the desired coordinate system would be to move the Crazyflie around in space to show what you want. The solution is to place the Crazyflie at certain positions and click a button to record data at these positions. The steps I have chosen are:

1. Place the Crazyflie at (0, 0, 0)
2. Place the Crazyflie on the X-axis, X > 0
3. Place the Crazyflie in the XY-plane, Y > 0
4. Move the Crazyflie around in the space with continuous recording of data

In this scheme the XY-plane is typically the floor.

Results

I have written basic implementations for both the Two Way ranging and TDoA modes and they seem to work reasonably well in simulations. I have also tested the Two Way ranging algorithm in our flight lab with mixed results. The solution converged in most cases but not always. When converging the estimated anchor positions ended up in the right region but some were off by up to a meter. Finally I did run the algorithm and fed the result into the system and managed to fly using the estimated positions which I find encouraging.

I will continue to work on this as a Friday Fun project and maybe it will make its way into the client code base at some point in the future? There are probably better ways to estimate the anchor positions and more clever algorithms, feel free to share them in the comments.

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.

Thanks to denis on the forum, there is also support for Crazyflie 2.0 in the PX4 flight controller firmware. PX4 is a comprehensive flight controller firmware used in research and by the industry.

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.

We are going to China and Maker Faire Shenzhen Nov 11-12.

Come and meet us in the Seeed Studio stand, we love talking to makers and geeks!

We have started working on a demo and the plan is to show an autonomously flying Crazyflie using the Flow deck for positioning. If you are in the area, drop by at Liuxiandong Campus, Shenzhen Polytechnic and say hi!

See you there!

Grasping objects is a hard task that usually implies a dedicated mechanism (e.g arm, gripper) to the robot. Instead of adding extra components, have you thought about embedding the grasping capability to the robot itself? Have you also thought about whether we could do it flying?

In the GRASP Laboratory at the University of Pennsylvania, we are concerned about controlling robots to perform useful tasks. In this work, we present the Flying Gripper! It is a novel flying modular platform capable of grasping and transporting objects with the help of multiple quadrotors (crazyflies) working together. This research project is coordinated by Professor Mark Yim and Professor Vijay Kumar, and led by Bruno Gabrich (PhD candidate) and David Saldaña (Postdoctoral researcher).

Inspiration in Nature

In nature, cooperative work allows small insects to manipulate and transport objects often heavier than the individuals. Unlike the collaboration in the ground, collaboration in air is more complex especially considering flight stability. With this inspiration, we developed a platform composed of four cooperative identical modules where each is based on a quadrotor (crazyflies) within a cuboid frame with a docking mechanism. Pair of modules are able to fly independently and physically connect by matching their vertical edges forming a hinge. Four one degree of freedom (DOF) connections results in a one DOF four-bar linkage that can be used to grasp external objects. With this platform we are able to change the shape of the flying vehicle during flight and use its own body to constrain and grasp an object.

Flying Gripper Design and Motion

In the proposed modular platform, we use the Crazyflie 2.0. Its battery life lasts around seven minutes, though in our case battery life time is reduced due to the extra weight. The motor mounting was modified from the standard design, we tilted the rotors 15 degrees. This was necessary as more yaw authority was required to enable grasping as a four-bar. However, adding this tilt reduces the lifting thrust by 3%. Axially aligned cylindrical Neodymium Iron Boron (Nd-FeB) magnets, with 1/8″ of diameter and 1/4″ of thickness are mounted on each corner enabling edge-to-edge connections. The cylindrical magnets have mass of 0.377g and are able to generate a force of 0.4 kg in a tangential connection between two of the same magnets. This forms a strong bond when two modules connect in flight. Note that the connections are not rigid – each forms a one DOF hinge.

The four attached modules results in a one DOF four bar linkage in addition to the combined position and attitude of the conglomerate. The four-bar internal angles are controlled by controlling the yaw attitude of each module. For example, two modules rotate clockwise and other two modules rotate counter-clockwise in a coordinated manner.

Grasping Objects

Collaborative manipulation in air is an alternative to reduce the complexity of adding manipulator arms to flying vehicles. In the following video we are able to see the Flying Gripper changing its shape in midair to accomplish the complex task of grasping a wished coffee cup. Would you like some coffee delivery?

This work was developed by:

Bruno Gabrich, David Saldaña, Vijay Kumar and Mark Yim

Additional resources at:

http://kumarrobotics.org/

http://www.modlabupenn.org/

So we are now back in the cold and dark Sweden after about a weeks visit to a warm and nice Shenzhen, China. Every time we go there something major has happened. When we visited last time, about a year ago, cash was king. Now apparently payments are done with QR codes, even in small lunch restaurants. And I was kind of proud about the BankID and Swish payments we have here is Sweden, until now… Another observation we did was that there are now a lot of colorful rental bikes which can be found about everywhere and which can be rented for around 1 RMB/hour. A great way of resource sharing and pushing Eco-friendly transportation. It has it downside though as piles of bikes could be commonly found and e.g. written about by theguardian.

Aside from the above observations the Maker Faire Shenzhen was one of the reasons we came to visit. As Shenzhen is called the “the silicon valley for hardware” we had pretty high expectations when coming to the Maker Faire. Even though it was a great Faire it did not really reach our high expectations but it is growing fast and I’m pretty sure in a couple of years it is the Maker Faire to be at. A quick summarize, robotics was one of the top categories of products on the faire. 3D printers which are popular on European and US faires was not that common which surprised us. Now let the pictures do the talking:

We exhibited on the faire sharing booth with Seeedstudio where we showed an autonomous sequence on top of a table using the flow deck. By pressing a button, the Crazyflie 2.0 would take of, fly in a circle, come back and land roughly in the same spot. It was a very engaging demo catching many peoples attention and especially the kids. The kids constantly wanted to press the button and interact with the Crazyflie.

All the interaction made us very happy and next time we will try to add the obstacle avoidance deck to make it even more engaging.

Unfortunately the Crazyradio PA is out of stock in our store and is estimated back around December 1. Until then please checkout our distributors for availability.

Modular robots can adapt and offer solutions in emergency scenarios, but self-assembling on the ground is a slow process. What about self-assembling in midair?

In one of our recent work in GRASP Laboratory at University of Pennsylvania, we introduce ModQuad, a novel flying modular robotic structure that is able to self-assemble in midair and cooperatively fly. This work is directed by Professor Vijay Kumar and Professor Mark Yim. We are focused on developing bio-inspired techniques for Flying Modular Robots. Our main interest is to develop algorithms and controllers for self-assembling modular robots that can dock in midair.

In biological systems such as ant or bee colonies, collective effort can solve problems not efficient with individuals such as exploring, transporting food and building massive structures. Some ant species are able to build living bridges by clinging to one another and span the gaps in the foraging trail. This capability allows them to rapidly connect disjoint areas in order to transport food and resources to their colonies. Recent works in robotics have been focusing on using swarm behaviors to solve collective tasks such as construction and transportation.Docking modules in midair offers an advantage in terms of speed during the assembly process. For example, in a building on fire, the individual modules can rapidly navigate from a base-station to the target through cluttered environments. Then, they can assemble bridges or platforms near windows in the building to offer alternative exits to save lives.

ModQuad Design

The ModQuad is propelled by a quadrotor platform. We use the Crazyflie 2.0. The vehicle was chosen because of its agility and scalability. The low-cost and total payload gives us an acceptable scenario for a large number of modules.

Very light-weight carbon fiber rods connected by eight 3-D printed ABS connectors form the frame. The frame weight is important due to tight payload constraints of the quadrotor. Our current frame design weighs 7g about half the payload capability. The module geometry has a cuboid shape as seen in the figure below. To enable rigid attachments between modules, we include a docking mechanism in the modular frame. In our case, we used Neodymium Iron Boron (NdFeB) magnets as passive actuators.

Self-Assembling and Cooperative Flying

ModQuad is the first modular system that is able to self-assemble in midair. We developed a docking method that accurately aligns and attaches pairs of flying structures in midair. We also designed a stable decentralized modular attitude controller to allow a set of attached modules to cooperatively fly. Our controller maximizes the use of the rotor forces by generating the maximum possible moment.

In order to allow the flying structure to navigate in a three dimensional environment, we control thrust and attitude to generate vertical and horizontal translations, and rotation in the yaw angle. In our approach, we control the attitude of the structure in a decentralized manner. A modular attitude controller allows multiple connected robots to stably and cooperatively fly. The gain constants in our controller do not need to be re-tuned as the configurations change.

In order  to dock pairs of flying structures in midair, we propose to have two flying structures: the first one is hovering and waiting, meanwhile the second one is performing a docking action. Both, the hovering and the docking actions are based on a velocity controller. Using a velocity controller, we are able to dock multiple robots in midair. We highlight that docking robots in midair is one of the fastest ways to assemble structures because the building units can rapidly move and dock in three dimensional environments. The docking system and control has been validated through multiple experiments.

Our system takes advantage of robot swarms because a large number of robots can construct massive structures.

This work was developed by:

David Saldaña, Bruno Gabrich, Guanrui Li, Mak Yim, and Vijay Kumar.

Additional resources at:

http://kumarrobotics.org/

http://www.modlabupenn.org/

http://davidsaldana.co/

As I wrote about in a previous blog post, I have been working on an anchor position estimation algorithm in the Crazyflie Client. The algoritm uses ranging data from the Loco Positioning system to estimate where the anchors are located, and thus remove the need to measure their positions in the room. I have finally reached a point where I think it is good enough to let it out from the lab and it has been pushed to the client repository.

A button has been added to the Loco Positioning tab that opens a wizard. In the wizard the user is asked to place the Crazyflie in certain positions to record ranges and define the coordinate system. If all goes well, the estimated anchor positions are transfered to the anchor position fields in the Loco Positioning tab. If the user is happy with the result the next step is to write the positions to the anchors and start flying!

Now to the disclaimer: the results may not always be perfect – surprise! We have not tested the algorithm a lot but it seems to give decent results, at least it can be useful as a base for manual corrections and sanity checks. Some of the estimated positions are pretty good, while others might be a meter or so off. The conclusion is that you should not trust it blindly, check that the estimated positions seem reasonable before flying.

Currently the system only supports Two way ranging, but extending it to TDoA should not be too complicated. There are probably many possible improvements that can be done, and we hope that everyone that finds this interesting and have ideas of how to do it will give it a go. After all, it is open source and we would love to see contributions refining the functionality, now that there is a base to build from.

Any feed back is welcome, let us know if it works or not in your setup!

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.

We’ve been seeing an increase in the demand for a “programmable drone”, where users can easily give simple commands though scripting and the Crazyflie 2.0 following them. In order for this to work well you need a closed-loop control, i.e you need a reference system to see how you’re moving. Previously this was only possible using external camera systems or bulky on-board cameras. But a while ago we released the Flow deck which solves this problem. Thanks to the mouse-like sensor the deck contains it enables the Crazyflie 2.0 to see how it’s moving along the floor. Suddenly it’s possible to give commands like “move 1 m forward” or “fly in a clock wise circle with the radius of 1 m”.

To make it easier for users to pick out the parts needed we’ve put together a discounted STEM drone bundle. It contains all the parts needed for scripting the flight. If you have a gamed-pad or a Bluetooth LE enabled phone you can of course fly it manually as well

To quickly get up and running, we have written a getting started guide. There is also a great hackster project, Beginner’s Guide to Autonomous Quadcopters by community member Chathuranga Liyanage, containing more details.

This year we decided to celebrate the holiday by painting a Christmas tree, rather than dressing one like last year. What better way to do this that with the flow deck,  a LED-ring and a long exposure photo. To check out all the yummy details and how to DIY check out this hackster project we made. Also as an Christmas extra we made this light painting video with the LED-ring mounted on top of the Crazyflie 2.0 and a bit of video editing. To be able to mount the LED-ring on top we hacked together an inverting deck. Not a bad idea and something we aim to release in the future!

Getting started

For those of you that was lucky and got a Crazyflie 2.0 under the Christmas tree, here is a short intro to get you started.

You can find all our getting started guides in the “Tutorials” menu on www.bitcraze.io. Take a look at “Getting started with the Crazyflie 2.0” to see how to assemble the kit and take off for your first flight. If you have an expansion deck you will also find a guide for how to install it.

Development

When you are comfortable flying the Crazyflie you might feel that it is time for the next step, to make use of the flexibility of the platform. After all it is designed to be modified!

Check out the “Getting started with development” tutorial to set up your development environment, build your first custom firmware and download it to the copter.

Maybe you want to add a sensor or some other hardware? Heat up your soldering iron and dive in to it! Find more information about the expansion bus on the wiki. The wiki is the place to look for all product and project documentation.

All source code is hosted on github.com/bitcraze and this is also where you will find documentation related to each repository. 

Projects

Looking for inspiration for a project? Take a look at hackster.io or read our blog posts. The video gallery contains some really cool stuff as well as our You Tube channel.

Contribute!

Open source is about sharing, creating something awesome together and contribute to the greater good! Whenever you do something that you think someone else could benefit from, please contribute it! If you were curious or confused about something, someone else probably will too. Help them by sharing your thoughts, insights and discoveries.

Why not

• Answer a question on the forum
• Add a hack to hackster.io
• Submit a pull request to on of the repos on github
• Add an issue to one of the repos on github with a suggestion for an improvement or a bug report. Or maybe get involved in the discussion on an issue?
• Add or update the wiki
• Improve www.bitcraze.io
• Comment a blog post

Need help?

Can not find the solution to a problem? Don’t understand how or what to do? Have you read all documentation and are still confused? Don’t worry, head over to the forum and check if someone else had the same problem. If not, ask a new question on the forum and get help from the community.

Happy holidays from the Bitcraze team!

It is now the first day in 2018 and a good day to look back at 2017. Its been a busy year as always and we have had a lot of fun during the year. One of the first things popping up is that things takes so much longer then we think. Luckily we are working with open source and the progression is not only dependent on us as we have awesome help from the community. We are already really excited about what’s coming in 2018, looking forward to working together with so many great people!  

Community

The Crazyflie 2.0 is still gaining attention and are becoming more and more popular among universities around the world. We see interest from researchers working with autonomous systems, control theory, multi-agent systems, swarm flight, robotics and all kinds of research fields, which is really great. This means that a lot of exciting work have been contributed by the community, so here is a small summary of what has happened in the community during the year.

In the beginning of the year the Multi-Agent Autonomous Systems Lab at Intel Labs shared how the Crazyflie 2.0 is used in their research for trajectory planning in cluttered environments. We wrote a blog post about this if you want learn more about their work. The Crazyflie showed up on the catwalk of Berlin Fashion week being part of fashion designer Maartje Dijkstras futuristic creation TranSwarm Entities”, a dress made out of 3D prints accompanied by autonomously flying Crazyflies.

For the third year Bitcraze visited Fosdem. We had a good time and got to hang out with community members like Fred how did a great presentation about what’s new in the Crazyflie galaxy. During the conference we took the opportunity to present the Loco positioning system and demo autonomous flight with the Crazyflie controlled by the Loco positioning system. In the demo we flew with the non-linear controller from Mike Hammer using trajectory generation from Marcus Greiff. 

We have had a few interesting blog post contributions during the year from major universities. Including a guest post written by researchers at Carnegie Mellon University. The researchers are using the Crazyflie 2.0 drone to create an adaptive multi-robot system. Similar work has been done by the researchers at the Computer Science and Artificial Intelligence Lab at MIT were they have been studying coordination of multiple robots, developing multi-robot path planning for a swarm of robots that can both fly and drive.

We have also had two interesting guest blog post from the GRASP Laboratory at University of Pennsylvania, the “A Flying Gripper based on Modular Robots” and “ModQuad – Self-Assemble Flying Structures“. Inspired by swarm behavior in nature, for instance how ants solve collective tasks, both projects explore the possibilities of how multiple Crazyflies can work together to perform different missions.

During the fall Fred took the time to pay us a visit at the office in Sweden and worked together with us. 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. 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. 

Some other great news is that 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.

Thanks to denis on the forum, there is now support for Crazyflie 2.0 in the PX4 flight controller firmware. PX4 is a comprehensive flight controller firmware used in research and by the industry.

Finally 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.

Hardware

During 2017 we released four new products. Beginning with the Micro SD-card deck which e.g. makes high speed logging possible. Then the Z-ranger that enables a height hold flight mode up to 1m above ground. We like to call it drone surfing as that is very much what it feels like when flying. We ended by releasing two boards, Flow deck and Flow breakout, in collaboration with Pixart containing their new PMW3901 optical flow sensor. The Flow deck enables scriptable flight which is very exiting. That lead us to release the STEM drone bundle which we hope will inspire people to learn more about flying robotics.

Hardware prototypes, our favorite sub-category, are something we have plenty of lying around here at the office. To name a few, a possible Crazyradio 2, the Loco positioning tag, the Crazyflie RZR, the Glow deck or Obstacle avoidance/SLAM deck. It takes a long time making a finished product… Hopefully we will see more of these during 2018!

Software

At the same time we released the Flow deck we also released the latest official Crazyflie 2.0 FW and client (2017.06). This enables autonomous capabilities as soon as the Flow deck is inserted by automatically turning on the corresponding functionality. Just before that, the loco positioning was brought out of early access with improved documentation and simplified setup. Since then a lot of work has been put into making a release of TDoA and improving overall easy of use. With the TDoA2 and automatic anchor estimation starting to work pretty well we should not be far from a new official release!

We would like to end 2017 with a big thank you to our users and community with this compilation video. Make sure to pump up the volume!

video link

This week we have a guest blog post by Ben, enjoy!

I’m Ben Kuperberg and i’m a digital artist, artist-friendly software developer and orchestra conductor. Being a juggler, I’ve decided to focus some of my work on the intersection between juggling and technology, and i’ve since been working more and more with jugglers, my last project being “Sphères Curieuses” from Le Cirque Inachevé, created by Antoine Clée. While the whole project is not focused on drones, a part of it involves synchronized flight of multiple drones and precise human interaction with those drones. Swarm flight is something already out there and some solutions already exist but the context of this project added some challenges to it.

Most work on drone swarms have been done by research group or school. They use high-grade expensive motion-capture system able to track precisely the drones and able to assign their absolute positions. While the quality of the result is undeniable, it’s not fit for stage shows : the setup is taking a lot of time which we can’t always have when the show is on the road. Moreover, the mocap system is too invasive for the stage if you want to be able to “hide” a bit the technology and let the spectator focus on what the artist wants you to see. Not to mention it costs an arm and a leg and Antoine needs both to juggle.

So we had to find other ways to be able to track multiple drones. That’s when we found out the [amazing] team at Bitcraze was working on the TDoA technology, which allows precise-enough tracking of a virtually unlimited amount drones, at reduced cost and with a fast and clean setup.

After some work we managed to have a first rough version of our swarm server made by Maxime Agor that allowed to connect and move multiple drones using the TDoA system, controlled from a Unity application.

While we were able to present a decent demo with this system, we were facing a major problem of reactivity. When working with artists and technology, reactivity is a key component to creativity. Because it can be frustrating and tense to stop each 2 minutes to make changes or fix problems. My first priority was therefore to prepare and design softwares that will allow me to spend most of the “creation time” on the actual creation aspect and not on technical parts. It is also essential that the artist performing in front of the audience can entirely focus on the performance and by fully confident in this technology. The last challenge is that as I focus my work on the creation and not touring, all my work needs to be easily understood and modified by both the artists and the technicians who will take over my work for the tour.

With all of that in mind, I decided to create a software with a high-end user interface called “La Mouche Folle” (« The Crazy Flie » in french) that allows to control multiple drones and have an overview of all the drones, their battery/charging/alert states, auto-connect / auto-reboot features, external control via OSC, and a Unity client to view and actually decide how to move the drones. All my work is open-source, so you can find the software on github.

There only is a Windows release for now but it should compile just fine on OSX and Linux, the software is made with JUCE, depends on OrganicUI and lib-usb. Feel free to contact me if you want more information on the software. Many thanks Wolfgang Hoenig for the support and the great work on the crazyflie cpp library i’m relying on.

So this is the basic setup of our project, but we needed more than that to control the drone. We wanted to be able to control them in the most natural way possible. We quickly decided to go with glove-base solutions, and have been working with Specktr to get our hands – pun intended – on developer versions of the glove. The glove is good but can’t give us absolute position of the hand, so we added HTC Vive trackers with the lighthouse technology and then were able to get both natural hand control and sub-millimeter precision of the tracked hand.

Then it was a matter of connecting everything together : for other projects for Theoriz Studio, I already developed MrTracker (used in the MixedReality project) that acts as a middleware between the Vive trackers and Unity.

I used Chataigne to easily connect and route the Specktr Glove data to Unity as well so we would have maximum flexibility to switch hardware or technology without breaking whole setup if we needed to.

In the past years, i’ve come to work on a lot of different projects, with different teams, which i like very much, because each project leads to discover new people, new ways of working and new challenges to overcome. I’m having a great time working on this project and especially sharing everything with the guys at Bitcraze and the community, everyone has been so cool and nice. I’ve planned to go at the Bitcraze studios to work for few weeks with them and i’m sure it’ll be a great experience !