Out of Control

2020-02-03 | Kimberly McGuire | 2 Comments

Two weeks ago, we had a blogpost about the state estimators that are available within the Crazyflie. So once the Crazyflie knows where it is, it would need to be determined where it wants to go, by means of the high level commander (implemented as part of the crazyswarm project) or set-points given by CFclient or directly from scripts using Crazyflie python lib. But exactly how would the crazyflie get to those desired positions in the first place? The differences between the current state estimates and the desired state, will need to be transformed to inputs given to the motors. Unfortunately, quadrotors like the Crazyflie do not have easy dynamics to maintain, so if you want to learn more, see this blogpost to read more about it!

So in order use the thrust of the motors in an useful way to get the Crazyflie to do what you want to do, there are several controllers to consider, which you can see on this quick overview here underneath. It shows the different control paths that can be taken from the high level commander all the way to the power distribution of the motors. Bear in mind that these are still simple representations and that the actual implementation is of course a bit more complicated, but at least it will give you a rough idea of which paths are possible to pursue.

PID Controller

So the default settings in the Crazyflie firmware is the proportional integral derivative (PID) control for all desired state aspects. So the High Level Commander (HLC) will send desired position set-points to the PID position controller (which used to be done off-board, so outside of the Crazyflie firmware before this blogpost). These result in desired pitch and roll angles, which are sent directly to the attitude PID controller. These determine the desired angle rates which is send to the angle rate controller (which is… you guessed… also a PID controller). This is also called Cascaded PID controller. That results in the desired thrusts for the roll pitch yaw and height that will be handled by the power distribution by the motors. (Note that height is mostly handled by the position controller)

INDI Controller

So the Incremental Nonlinear Dynamic Inversion (INDI) controller is an controller that immediately deal with the angle rates to determine the trust. This is a very new addition to the Crazyflie firmware by one of our community members and is based on the implementation of this paper. Currently, the position control is still handled by the same PID controller mentioned in the last paragraph, Nevertheless for handling the angles, it should be faster than the attitude and rate PID controller combined. We have not yet fully tested this out but if you do, let us know how you like it on the Bitcraze forum!

Mellinger Controller

As part of the Crazyswarm project, the controller designed by Daniel Mellinger has been implemented in the Crazyflie firmware as well. Please see this paper about the details of the Mellinger controller. It is a sort of “all in one”: based on the desired position and velocity vectors towards those position, it will calculate right away what the desired thrusts are that need to be distributed to all the motors. This results in a much smoother controlled trajectory of the high level commander and therefore advised to use when the Crazyflie has a precise position estimate (lighthouse and mocap). However, as it is so aggressive, any position estimate of a lesser quality (flowdeck or LPS) will not be sufficient for this controller. See some examples of mellinger controlled flights here and here.

Let us know what you think!

So do you have experience working with these controllers or want to know more about them, please drop us a message on the forum! We are currently working on stabilization and documentation of multiple aspects of the Crazyflie and the controllers is one of them, so we are really interested what your experiences are!

Welcome to our new team member, Barbara Rousselot

2020-01-27 | Barbara | Leave a comment

Hello there !

My name is Barbara, and I’m really proud to say I’m the new member of Bitcraze. As of now, I will be dealing with everything non-technical, so that the great minds here can focus on creating more of their amazing products!

If you want to know a little more about me, I should start by the beginning. I come from France originally, but have moved a lot over the years. From my early childhood in Tunisia to my semester abroad in Canada, I never really settled down… Until I came to Sweden, a little over 5 years ago. After having lived in Paris for some time, Malmö was a much needed breath of fresh air. In France I worked on a lot of different fields: receptionist, assistant, salesperson, teacher’s assistant, even as an actress. Those different experiences broadened my horizon and taught me a lot. Most of all, I learned to follow my passions: helping people, singing, and generally loving what I’m doing. My last assignment included community management and content creation in a video game company, but I’m happy to use every bit of my 5 years experience as an administrative assistant to be the office wizard here at Bitcraze.

When I’m not taking care of my family or working, I keep on following my passions. I could talk hours about movies or books (especially about Terry Pratchett books, or musicals, my favorite type of movies!). I took up knitting a year ago and can’t put my needles down now. And I consider myself a real geek. Video-games, movies, comics, I even learned some programming over the years (even tough I can’t compare with the other team members!). My greatest challenge last year was to build my own PC, and I have to say that I managed it with flying colours. Another way I past the time (while making everyone happy) is by baking, and every time a new batch of cookies gets out of the oven, I feel the weight of the family tradition: my grandfather was a french pastry cook, and I proudly follow his footsteps (and recipes!).

I’m really happy to join the Bitcraze team and excited about the future. I hope I’ll learn a lot from working with Arnaud, Kristoffer, Kimberly, Marcus and Tobias. My girly-geek side can’t stop jumping with excitement at working in such an impressive and stimulating environment.

Fosdem 2020

Arnaud is going to Fosdem this weekend, check out his forum post and say hi if you are there.

State estimation: To be or not to be!

2020-01-20 | Kimberly McGuire | 2 Comments

How does a Crazyflie manage to fly and stay in the air in the first place? Many of us tend to take this for granted as much research tend to happen on the application level. Although we try to make the low level elements of flight as stable as possible, it might happen that whatever you are trying to implement on the application level actually effects the Crazyflie on the low level controls and estimation. We therefore would like to focus a little bit on the inner-workings of the autopilot of the Crazyflie, starting with state estimation. The state estimation is part of the stabilizer loop in the Crazyflie, an overview of is was made in a previous blog post.

State estimation is really important in quadrotors (and robotics in general). The Crazyflie needs to first of all know in which angles it is at (roll, pitch, yaw). If it would be flying at a few degrees slanted in roll, the crazyflie would accelerate into that direction. Therefore the controller need to know an good estimate of current angles’ state and compensate for it. For a step higher in autonomy, a good position estimate becomes important too, since you would like it to move reliably from A to B.

There are two types of state estimators in the crazyflie firmware, namely a Complementary Filter and an Extended Kalman Filter.

Complementary Filter

The complementary filter is consider a very lightweight and efficient filter which in general only uses the IMU input of the gyroscope (angle rate) and the accelerator. The estimator has been extended to also include input of the ToF distance measurement of the Zranger deck. The estimated output is the Crazyflie’s attitude (roll, pitch, yaw) and its altitude (in the z direction). These values can be used by the controller and are meant to be used for manual control. If you are curious how this code is implemented exactly, we encourage you to checkout the firmware in estimator_complementary.c and sensfusion6.c. The complementary filter is set as the default state estimator on the Crazyflie firmware.

Extended Kalman Filter

The (extended) Kalman filter is an step up in complexity compared to the complementary filter, as it accepts more sensor inputs of both internal and external sensors. It is an recursive filter that estimates the current state of the Crazyflie based on incoming measurements (in combination with a predicted standard deviation of the noise), the measurement model and the model of the system itself. We will not go into detail on this but we encourage people to learn more about (extended) Kalman filters by reading up some material like this.

Shortly said, because of the more state estimation possibilities, we preferred the Kalman filter in combination with several decks: Flowdeck, Loco positioning deck and the lighthouse deck. If you look in the deck driver firmware (like for instance this one), you see that we set the required estimator to be the Kalman and that is of course because we want position/velocity estimates :). Important though is that each input of the measurement effects the quality of the position, as positioning of the Lighthouse deck (mm precision) is much more accurate that the loco positioning deck (cm precision), which has all to do with the standard deviation of the measurement of those values. Please check out the content of estimator_kalman.c and kalman_core.c to know more about the implementation. Also good to know that the Kalman filter has an supervisor, which resets if the position or velocity estimate is gets out of hand.

Of course this blogpost does not show the full detailed explanation of state estimation, but we do hope that it gives some kind of overview so you know where to look if you would like to improve anything. The Kalman filter can easily be extended to accept more inputs, or the models on which the estimates are based can be improved. If you would like implement your own filter, that would be perfectly possible to do so too.

It would be great if you guys could share your thoughts and questions about the state estimation on the crazyflie on the forum!

Crazyflie Bolt: FPV meets Autonomy

2020-01-13 | Sean Kelly | 4 Comments

I started working with the Crazyflie 2.0 in 2015. I was interested in learning how to program a quadcopter, and the open-source nature of the Crazyflie’s hardware and software was the perfect starting point.

Shortly after, I discovered the world of FPV and the thrill of flying with a bird’s eye view. My journey progressed from rubber-banding an all-in-one camera/VTX to my Crazyflie, to building a 250mm racing quad (via the BigQuad deck), and into the world of Betaflight (including bringing Betaflight support to the Crazyflie hardware).

: FPV for Beginners ;)

: BigQuad Build

Naturally, the announcement of the Bolt (then known as the RZR) piqued my interest, and the folks at Bitcraze graciously allowed me early hands-on with the product.

This post details my progress towards building out a FPV-style drone on top of the Crazyflie Bolt.

Component List

The FPV community has come a long way since 2015. What once was a very complicated process is now well documented and similar to building a PC (well, with some soldering). For latest details on the specifics of building FPV drones, I recommend resources such as Joshua Bardwell or the r/Multicopter subreddit.

Turns out I had enough components lying around for a 4-inch (propeller diameter) build based on 3S (3 cell) LiPo batteries. Again, there’s nothing special about these parts (in fact they’re all out of date). Take this list as a guide, and do your own research.

PDB (Power Distribution Board): This is a circuit board that produces regulated voltages from an unregulated LiPo battery. The Bolt has built-in regulators but is only rated up to an 8A current draw per motor. My 4 inch propellers will certainly draw more than 8A, and so an external PDB is required (plus having dedicated 12V and 5V supplies is nice for peripherals).
4x DYS 1806 Brushless Motors: Brushless motors use magnetic pulses to rotate a motor bell (distinct from brushed motors found on the regular Crazyflie).
4x DYS 20A BLHeli_S ESCs (Electronic Speed Controller): This is a piece of circuitry that accepts a logic-level control signal and applies direct battery power to motor coils to make a brushless motor spin. They have to be rated for the current draw expected by the battery+propeller combination.
Tweaker (by Shendrones) Frame: I’ve been wanting to build a quad around this frame, and the large square hole is interesting for the Bolt (more on that later). One thing to keep in mind is this is an ‘H’ style frame. That is, it’s longer than it is wide, so flight will not be perfectly symmetrical. If you’re interested in building a larger Crazyflie and not so interested in FPV, you’ll definitely want a symmetrical ‘X’ style frame.
WS2812B addressable LEDs: LEDs are proven to make things better. It’s science.
Camera + VTX: For a full FPV setup, you’ll need a camera and a video transmitter. For the most part these run completely independently of the flight controller and so I’ll omit them from this article — what I’ve shown in the picture above is horribly out of date anyway.
RX: Radio receiver. For longer range flights and reduced latency it may be a good idea to use an external radio and UART-based receiver with diversity antennas. However, some specific work went in to the Bolt’s antenna design, so I’ll be sticking with the on-board NRF51 and external antenna.
Flight Controller: The Crazyflie Bolt!

The Build

Again, there are hundreds of fantastic guides on the web that detail how to build an FPV quadcopter. Instead of trying to create another, here are some notes specific to my Bolt build.

Expansion Decks

Since the Bolt is pin compatible with the Crazyflie, I thought it would be interesting to try and take advantage of a couple existing Crazyflie expansion decks in my build: The LED Ring Deck, the Flow Deck v2, and the Micro SD Card Deck.

The LED Ring Deck

The LEDs were the most hands-on feature to enable. Rather than simply attaching the LED ring inside the frame, I mounted a series of WS2812B lights to the underside of my frame’s arms. The LED Ring Deck consists of 12 LEDs connected in series — so I put three LEDs on each arm of the frame and wired them up in a daisy-chain.

Finally, I soldered the lead to IO_2 (the same that’s used by the LED Ring Deck) on a Breakout Deck.

Since this isn’t the official LED Ring Deck, there’s no OW memory ID. The deck must be force-enabled by specifying a compile flag in your tools/build/make/config.mk file:

CFLAGS += -DDECK_FORCE=bcLedRing

With the custom firmware, the under-arm LEDs work just like the LED Ring Deck (other than the lack of front-facing LEDs).

Micro SD Card Deck

Most popular flight controllers feature flash storage or SD card slots for data logging. The FPV community uses storage to log sensor data for PID tuning and debugging. Naturally, this deck is a good fit on my Bolt build, and requires no additional modification.

Flow Deck (v2)

Remember my interest in the square cutout on my frame of choice? That, and my unorthodox choice to mount the Bolt board below my PDB, means I can theoretically use the bottom-attached Flow Deck to achieve some lateral stabilization while close to the ground. In theory, the VL53L1x ranger should work outdoors thanks to its usage of 940nm light as opposed to 850nm.

Note: This photo also shows the daisy chain wire connecting banks of LEDs in series

Other Build Tips

It’s good practice to soft mount flight controllers to minimize transferring motor/prop vibrations into the IMU. I used these to isolate the flight controller from the frame — not perfect, but better than a rigid mount.
The receiver antenna must be mounted clear of the carbon fiber frame and electronics. I like to use a heavy duty zip tie and attach the antenna with heat shrink.
The Bolt can be powered from a 5v regulator on your PDB, but if you want to take advantage of the VBat sensor it should be powered from the raw battery leads instead. However, most ESCs support active breaking (ability to slow/stop the propellers on demand). Active breaking is known to produce a lot of back-voltage, which can damage some circuits. To be safe, since I’m using a 3S battery (12.6V when fully charged, 11.1V when depleted) I chose to power the Bolt off a regulated 12V supply from my PDB. This way, the PDB’s regulator will filter out voltage spikes and help protect the Bolt. Readings won’t be accurate at the higher range, but what really matters for a voltage sensor is to know when to land.

Results

It works! There is work needed to improve flight, though:

Control tuning is required. The powerful brushless motors respond much quicker than brushed motors, and so many of the PID and/or Kalman parameters are too aggressive or just non-optimal.
Stabilization with the Flow deck does not work — I haven’t spent much time debugging but my guess is it’s either due to the Kalman tuning, or problems with the VL53L1x depth working outdoors (which also impacts the flow measurements)
Betaflight Support: Betaflight has no driver for the BMI088 IMU used on the Crazyflie Bolt or the Crazyflie 2.1.
Safety Features: Brushless quads are very dangerous and can cause serious injuries. It’d be good to implement a kill-switch and a more aggressive failsafe in the firmware to prevent flyaways.

All in all, this was an enjoyable project and I’m excited to see some autonomous brushed quads coming out of the Crazyflie community!

What’s up in 2020

2020-01-06 | Kristoffer Richardsson | Leave a comment

2020 has arrived! We are back after a long and nice holiday and are ready for new awesome year. So what’s happening in 2020 at Bitcraze?

Frequently we will go through a hectic period of releasing new hardware and adding new features that’s followed by a period of stabilization and maintenance. Since last fall we released a number of new products and added lots of new functionality to the Crazyflie, this spring it’s time to look back, finish up and make things more stable.

First up this year is to release a few of the products we didn’t manage to get out during the fall, the AI-deck and the Active marker deck. The first batches should be ready during the beginning of 2020 and we are really excited to see what our users will do with the new hardware.

Secondly we will be focusing on getting the Lighthouse deck out of Early Access. After the release last year we’ve added lots of functionality such as full pose using only a single base-station, but we’re still missing Lighthouse V2 support. In order to finish up we need to make the system easier to use and to add the V2 support.

The third thing we will be focusing on is stability and usability. We’re really happy about the ecosystem that exists around the Crazyflie platform. With lots of hard work and help/contributions from our community it’s become rather extensive over the years. But with the ecosystem and feature-set continuing to grow it’s not always easy to keep up.

The last thing we will be looking at is to continue adding more swarm-related functionality to simplify the task of flying multiple Crazyflies at the same time. Some of the features we’ve been discussing are: improved positioning, improved communication, drone health, trajectories and so on.

In order to handle the growing product portfolio and Crazyflie platform we’ll also continue growing the team during 2020. Hopefully there will more news on this already during the coming weeks :-)

With a long list of new customers, a growing ecosystem and lots of interesting things to come, we’re really looking forward to an exciting and fun year at Bitcraze! Oh, and as always there’s a few new hardware prototypes cooking… Happy New Year!

Looking back at 2019

2019-12-30 | Kristoffer Richardsson | Leave a comment

2019 is coming to an end and we are soon flipping the calendar to a new year. This is the last blog post of 2019 – time to look back and recap what has been going on during the year.

Community

We have had quite a few blog posts by community members this year. It is exciting for us to hear about the cool things our users are doing with our products, and we are happy to share them with all of you. If you have not read them yet and you might have some spare time during the holidays, it is well worth the time spent!

During 2019, we have also attended a number of conferences and events, where we have met a lot of interesting people, heard about amazing projects and got feedback from users. We attended FOSDEM (Belgium), ICRA (Canada), IMAV (Spain), ISRF (South Korea) and finally IROS (China).

Software

There have been quite a lot of improvements to the software in the Crazyflie ecosystem. Apart from bug fixes there has been some restructuring to simplify modifications and increase the utilization of system resources. The Crazyflie firmware has also been generalized to support multiple hardware platforms. We have added an app layer, Peer 2 Peer communication and support for new decks (see below).

The community has been buzzy contributing new and improved functionality as well as bug fixes to the software stack. Just to mention a few: support for new sensors, improved positioning support, better logging to SD-card, improved communication, new controllers and compressed trajectories. We can not express how grateful we are, thank you all!

Hardware

There have been quite some work on new hardware as well during 2019. We kicked the year off by releasing the two new platforms: the Crazyflie 2.1 and Roadrunner, and finished it by the recent release of the Crazyflie Bolt.

On the deck side there has been a focus on positioning support in the Passive– and Active marker decks that we have released in collaboration with our friends at Qualisys. The Lighthouse deck also falls into this category, we are excited about the performance and have high hopes of future awesomeness when it leaves Early access!

We have put a lot of work into the AI-deck during the year. Unfortunately we did not manage to finalize it 2019, but hopefully it should not be too long into 2020 until it is available in the store.

Documentation

Documentation is always hard, especially when the system is spread over many repositories. We have moved a fair amount of our documentation from the wiki to the code repositories to keep it closer to the code, and hopefully make it easier to keep it up to date. The documentation is now also published on the web to make it easy to access.

Logistics

We have tried out various 3d party shipping solutions earlier, but have settled on shipping our selfs, from our own warehouse in Sweden. This give us better control of the process and we have made a number of improvements and automated as much as possible to keep it lean and smooth.

Bitcraze

It has been an intense year for the Bitcraze family. We have moved to a new office with much more space and opportunities. It has required quite some work to set up labs, flight arena and other areas to our liking, but finally we have settled in and are very happy with the result!

Björn decided to leave the company in the beginning of the year, but on the other hand Kimberly joined in May! We have also had the great pleasure of hosing interns Victor and Zhouxin during the year.

On the system side, we have revamped our server platform for web, forum, wiki and internal services and are now using kubernetis. We also had a rapid increase in spam on the forum during the summer, but managed to counter it with better anti-spam tools.

Conclusions

It is a good exercise to look back and remember what we have done during the year. We are equally surprised each time we do this and realize all the things we have managed to squeeze in, only being 5 persons in the company! It has been yet another hectic year, but full of happiness and excitement.

Thanks for an awesome year!

Happy Holidays!

2019-12-23 | Kimberly McGuire | 1 Comment

Happy holidays to all our users, community members and friends! We are happy to announce our 2019 Christmas video which we have made in collaboration with Ben Kuper! It is starring 7 Crazyflies, the lighthouse positioning system, our office Christmas tree and a whole lot of holiday spirit, so go ahead and take a look!

Here are some words from Ben how it was to work on this year’s Christmas video at our office:

Coming to Bitcraze’s HQ and working with them has been once more a wonderful experience, technically and humanly ! The main goal of this session was to test and implement the new lighthouse tracking system in the tool suite I’m creating, and it was an amazing surprise to witness for real the uncanny stability of the drones when they’re on lighthouse tracking !

Of course, my first reaction was to push the limit and see what can be done with this new power, this is why I created this choreography : to see what can be done in a limited amount of time (1 and a half day to create the full choreography, the official video shows the first part only), and trying to go at the limit of the current possibilities. As the team was working on occlusion recovery, we decided to have the drone fly around the tree as a fun test, and it works !

In the new year we will have a followup blog-post going into detail on how exactly we made this video. Until then, happy holidays and have an awesome new year!

Production Tests

2019-12-16 | Arnaud | Leave a comment

We are currently finishing production test design for a couple of expansion decks and we figured we never wrote about it and about the more general board production process. In this blog post we wanted to talk a bit about how we test boards in the productions phase, taking as an example the forthcoming active marker deck.

When finalizing an electronic board, we send to the manufacturer documentation that allows to manufacture & assemble a, hopefully, functional board. Although we assume that the individual components are in working order, the problem is that the assembling is not always perfect, so we need to check that everything we do is actually working,. This is what the production test is solving.

The first thing is to find out what to test, for that we need a strategy. The strategy we have been using is to test every step where we have modified or work on: for example we will test all the connections we have soldered in the manufacturing process. We will normally not test all the functionalities of ready-made module. For example, following this strategy, we will usually test all communication interface we have cabled, but we will not test all functionalities of a microcontroller we solder on the board, these are deemed to be already tested and working by the microcontroller manufacturer. This step usually end up with an annotated schematic:

Once we know what to test and roughly how to test it, we document a test rig that will be able to run the tests automatically. Some tests are generic and applicable to all our boards, for example we do test voltages with a multi-meter on every board that has a regulator. Some tests are very board specific. For example, for the active marker deck we want to test IR LEDs and an IR detector, we define a test rig that has reflector to reflect the LED to the detector and we will use the onboard detector to test the LEDs:

Simple block diagram of the test rig for the ActiveMarker Deck

We are normally using a Crazyflie on all our test rig, since it is usually possible to test all functionality from the deck port. We also try as much as possible to integrate the test software into the real software. For the active marker deck it meant adding 38KHz modulated output mode to the LEDs in order to emit a signal detectable by the detector, which will make it to the final firmware. Finally, we have a test software, running on the test computer, that uses the Crazyflie python lib to talk to the Crazyflie and run the test. The last step of all the test is to write the deck One Wire identification memory so that it can be detected by a Crazyflie.

Screenshot of the test program for the test engineer

From these specification, the manufacturer can then build a test rig and start testing boards, non-passing board will be re-worked until they pass or discarded.

Test rig for the Multi-ranger expansion deck

What we have learned in our years at Bitcraze is that testing phase is the most important part of the development process of PCB. Therefore, the earliest we already start thinking about the production tests in the board design, the more smooth the final phase of production of our new products will be.

Crazyflie Bolt in store

2019-12-10 | Tobias | Leave a comment

The Crazyflie Bolt control board

After a couple of delays we are happy to announce the Crazyflie Bolt is now stocked and ready to ship out. For those of you that are new to the Bolt, it is basically a Crazyflie 2.1 control board, but built to fit a bigger package. We have blogged about it a couple of times before, so if you would like to catch up you can start from the first idea, to maturing and finally changing name from RZR to Bolt. Another way to describe the Bolt is: Crazyflie 2.1 + Big-quad deck in one which doesn’t hog any deck expansion pins. Thus combinations such as Bolt + Led-ring + Lighthouse-4 is now possible or e.g. Bolt + Flow v2 + LPS.

Keep in mind that the Bolt is an early access product so you will most likely have to dig in to the code to hard-code PID-tuning parameters etc. Also trowing a warning finger, heavier drones can be very dangerous so be sure to keep safe!

The Crazyflie Bolt is delivered as a stand alone control board. Frame, motors, propellers and battery needs to be added, for details check out the wiki. Unfortunately we don’t have a good reference kit to recommend at the moment. If you happen to have built a good one, please share.

Crazyflie Bolt Kit

Designing DroneChi

2019-12-02 | Joseph La Delfa | 1 Comment

This week we have a guest blog post from Joseph La Delfa.

DroneChi is a Human Drone interaction experience that uses the Qualisys motion capture system that enables the Crazyflie to react to movements of your body. At the Exertion Games Lab in Melbourne Australia, we like to design new experiences with technology where the whole body can be the controller and is involved in the experience.

When we first put these two technologies together we realised two things.

It was super easy to keep your attention on a the drone as it flew around the room reacting to your movements.
As a result it was also really easy to reflect on and refine ones own movements.

We thought this was like meditation meditated by a drone, and wanted to investigate how to further enhance this experience through design. We thought the smooth movements were especially mesmerising and so I decided to take beginner Tai Chi lessons; to get an appreciation of what it felt like to move like a Tai Chi student.

We undertook an 8 month design program where we simultaneously designed the form and the interaction of the Crazyflie. The initial design brief was pretty simple, make it look and feel light, graceful and from nature. In Tai Chi you are asked all the time to imagine a flower, the sea or a bird as you embody its movements, we wanted to emulate these experiences but without verbal instruction. Could a drone facilitate these sorts of experiences through it’s design?

We will present a summarised version of how the form and the interaction came about. Starting with a mood board, we collated radially symmetrical forms from nature to match a drone’s natural weight distribution.

We initially went with a jelly fish, hoping to emulate their “push gliiide” movement by articulating laser cut silhouettes (see fig c). This proved incredibly difficult, after searching high and low for a foam that was light enough for the Crazyflie to lift, we just could not get it to fly stable.

However, we serendipitously fell into the flower shape by trying to improve how we joined the carbon rods together in a loop (fig b below). By joining them to the main hull we realised it looked like a petal! This set us down the path of the flower, we even flipped the chassis so that the LED ring faced upwards (cheers to Tobias for that firmware hack).

Whilst this was going on we were experimenting with how to actually interact with the drone. Considering the experience was to be demonstrated at a major conference we decided to keep the tracking only to the hands, this allowed quick change overs. We started with cardboard pads, experimented with gloves but settled on some floral inspired 3D printed pads. We were so tempted to include the articulation of the fingers but decided against it to avoid scope creep! Further to this, we curved the final hand pads (fig d) to promote the idea of holding the drone, inspired by a move in Tai Chi called “holding the ball”.

As a beginner practicing Tai Chi I was sometimes overwhelmed by the number of aspects of my movement that constantly needed monitoring, palms out, heel out, elbow slightly bent, step forward etc. However in brief moments it all came together and I was able to appreciate the feelings of these movements as opposed to consciously monitoring them. We wanted this kind of experience when learning DroneChi so we devised a way of mapping the drone to the body to emulate this. After a few iterations we settled on the “mid point” method as seen below.

The drone only followed the midpoint (blue dot above) if it was within .2m of it. If it was outside of this range it would float away slowly from the participant. This may seem like a lot, but with little in the way of visual guidance (eg a laser pointer or an augmented display) a person can only rely on the proprioceptive feedback from their own body. We used the on board LED ring on the drone to let the person know at least when they are close, but that is all the help they got. As a result this takes a lot of concentration to get right!

In the end we were super happy with the final experience, in the study participants reported tuning into their bodies when using the drone, as well as experiencing a unique sort of relationship to the drone; not entirely like a pet and also like an extension of the body. We will be investigating both findings from the study through the design and testing of a new system on the Crazyflie. We see this work contributing to more intimate designs for human drone interactions as well as a being applicable to health contexts such as rehabilitation.