# Category: Random stuff

Hey, Victor here!

As some of you may know, I’ve worked at Bitcraze for two summers (2019, 2020), and I did my Bachelor’s thesis here during the spring this year. While we mentioned shortly that I started working on my thesis (here), I never presented the results of it, so I thought that I’d do that now! Better late than never, right?

So, during my thesis I built a prototype deck for the Crazyflie which contained five multizone lidar sensors (VL53L5CX) and an ESP32-S3. The VL53L5CX sensors can output distances to a 8×8 grid, with a 45 degrees FoV at a rate of 15 hz. The purpose of the ESP32-S3 was to collect the data from the sensors and send it to a ground control station, either with WiFi, or, with the nRF radio on the Crazyflie. While the ESP32-S3 is quite overkill for only collecting data and send it, we weren’t sure of how much data that would be gathered from the sensors, so to be on the safe side we rolled with the ESP32-S3. Both the sensors and the microcontroller was very new at the time so it seemed like a good oportunity to try them out.

I designed the schematic in KiCad and got a lot of help from everyone here at Bitcraze while doing so, especially Tobias. Once the schematic was done I designed the PCB, ordered the components and then waited eagerly for the stuff to arrive. Once everything had arrived, I soldered all components and assembled the deck. I then wrote some firmware for the ESP32-S3, and the STM32 on the Crazyflie, and at last I wrote a simple GUI in PyQt to help visualize the data, both in 2D and 3D.

The deck was quite successful and while the GUI was very far from perfect, I think it did show that the deck has some nice potential and it was very cool to see the 3D point cloud in realtime while flying the Crazyflie! I tried sending the data over WiFi which worked perfectly well, and I also tried sending it through the nRF on the Crazyflie with the help of CPX, which also worked pretty well.

If you’re more curious about the thesis, feel free to check it out here, and the github repository can be found here.

I finished the thesis in the beginning of the summer, and I have been working part time here at Bitcraze since September and I’ve truly been loving! I think it’s been really cool to become a part of the team and work more on the regular stuff that the rest of the team does. It has been very interesting to see how the team works and cooperates on a daily basis. Something that striked me was just how many products and different features and services we handle here, with only six people!

Fortunately and unfortunately, I will be moving to Gothenburg next week which means that my time at Bitcraze is over, for this time. I have learned a lot from everyone here and truly appreciate all the love and support, which actually started before I even started my Bachelor’s degree.

Cheers and (early) Merry Christmas,
Victor

As you have been very much aware of already if you have been reading the blog occasionally is that we went to Japan with the entire company to be at the International Conference on Intelligent Robots and Systems (IROS) in Kyoto, Japan. Besides eating great food, singing karaoke, and herding our fully onboard autonomous swarm at our stand, we also had some time to check out what kind of work was done with the Crazyflie in the proceeding papers and talks!

So just some generic statistics first:

• IROS had 1716 papers accepted
• We found 14 Crazyflie papers/posters and 2 workshop papers
• The three biggest topics we found the papers in were: SLAM, Multi-robot systems and Navigation & Motion planning, SLAM

At ICRA this year, we noticed that the Crazyflie/bolt were used to make unconventional platforms, like a mono-copter or transforming the Crazyflie to a Pogo stick. It was interesting to see that now at IROS, the focus seemed to be more on navigation, localization and even SLAM… also with unconventional sensors!

## Navigation and SLAM with the Crazyflie

In the summer I (Kim) worked on a summer project with using ROS2 to try SLAM with the standard packages with the Flow deck and Multi-ranger. This was also to present the work at ROScon before that with the Crazyswarm2 project, the Crazyflie can be used as an actual robotic platform too! I’m glad that some researchers already figured this one out already, as there were quite some papers on SLAM! [6] and [12] made use of the flow & multi-ranger but made their own custom algorithms to do SLAM and mapping that was more tailored to the task than the standard SLAM packages out there meant for 360 degree lidars.

Very interestingly, there were several papers that uses unconventional sensors for this as well. [5] used a gas sensor to do both gas source localization and distributing mapping and [10] made their own echolocation deck with buzzer + microphones. Let’s see what other sensors will be explored in the future!

## Safe Robot Learning Competition

A special mention goes to the Safe Robot Learning competition, organized by the joined TU Munich and Utoronto’s the Learning system & robotics lab (formally known as the Dynamic Systems lab). In this competition, teams could participate with an online competition where they had to finish an obstacle course in simulation. From those that were successful, the finals were done with a real Crazyflie at a remote testbed in the University of Toronto, where the algorithms were put to the ultimate test! The simulation was done in the safe-control-gym framework [12], and the communication with the real Crazyflie was done with the ROS1 based Crazyswarm. We sponsored the first three places with a couple of Crazyflie bundles, so congrats to the winners!

## List of IROS 2022 Papers featuring the Crazyflie

1. Using Simulation Optimization to Improve Zero-shot Policy Transfer of Quadrotors Sven Gronauer, Matthias Kissel, Luca Sacchetto, Mathias Korte and Klaus Diepold
2. Downwash-aware Control Allocation for Over-actuated UAV Platforms Yao Su , Chi Chu , Meng Wang , Jiarui Li , Liu Yang , Yixin Zhu , Hangxin Liu
• Beijing Institute for General Artificial Intelligence (BIGAI)
• ArXiv
• IEEE Xplore
3. Towards Specialized Hardware for Learning-based Visual Odometry on the Edge Siyuan Chen and Ken Mai
• Beijing Institute for General Artificial Intelligence (BIGAI)
• IEEE Xplore
4. Polynomial Time Near-Time-Optimal Multi-Robot Path Planning in Three Dimensions with Applications to Large-Scale UAV Coordination Teng Guo, Siwei Feng and Jingjin Yu
5. GaSLAM: An Algorithm for Simultaneous Gas Source Localization and Gas Distribution Mapping in 3D Chiara Ercolani, Lixuan Tang and Alcherio Martinoli
• Ecole Polytechnique Federale de Lausanne (EPFL),
• IEEE Xplore
6. Efficient 2D Graph SLAM for Sparse Sensing Hanzhi Zhou, Zichao Hu, Sihang Liu and Samira Khan
7. Avoiding Dynamic Obstacles with Real-time Motion Planning using Quadratic Programming for Varied Locomotion Modes Jason White, David Jay, Tianze Wang, and Christian Hubicki
8. Dynamic Compressed Sensing of Unsteady Flows with a Mobile Robot Sachin Shriwastav, Gregory Snyder and Zhuoyuan Song
9. A Framework for Optimized Topology Design and Leader Selection in Affine Formation Control Fan Xiao, Qingkai Yang, Xinyue Zhao and Hao Fang
10. Blind as a bat: audible echolocation on small robots Frederike Dumbgen Adrien Hoffet Mihailo Kolundzija Adam Scholefield Martin Vetterli
• Ecole Polytechnique Federale de Lausanne (EPFL)
• IEEE xplore
11. Safe Reinforcement Learning for Robot Control using Control Lyapunov Barrier Functions Desong Du, Shaohang Han, Naiming Qi and Wei Pan
• Harbin Institute of Technology + TU Delft + University of Manchester
• Late breaking result poster
12. Parsing Indoor Manhattan Scenes Using Four-Point LiDAR on a Micro UAV Eunju Jeong, Suyoung Kang, Daekyeong Lee, and Pyojin Kim
• Sookmyung Women’s University,
• Late breaking result poster
13. Interactive Multi-Robot Aerial Cinematography Through Hemispherical Manifold Coverage Xiaotian Xu , Guangyao Shi , Pratap Tokekar , and Yancy Diaz-Mercado
• University of Maryland
• Note: Only mention of Crazyflie experiments in presentation
14. Safe-control-gym: a Unified Benchmark Suite for Safe Learning-based Control and Reinforcement Learning in Robotics Zhaocong Yuan, Adam W. Hall, Siqi Zhou, Lukas Brunke, Melissa Greeff, Jacopo Panerati, Angela P. Schoellig
15. Distributed Geometric and Optimization-based Control of Multiple Quadrotors for Cable-Suspended Payload Transport Khaled Wahba and Wolfgang Hoenig
16. Customizable-ModQuad: a Versatile Hardware-Software Platform to Develop Lightweight and Low-cost Aerial Vehicles Diego S. D’Antonio, Jiawei Xu, Gustavo A. Cardona, and David Saldaña

Let us know if we are missing any papers or information per papers! Once the IEEE xplore IROS 2022 proceedings have been published, we will update these too and put them on our research page.

Hey, Victor here!

I’ve been flying FPV drones for some time and while I usually fly bigger drones (3-5 inch props) I have always wanted to put an analog camera on the Crazyflie to fly it in FPV. So, a few weeks ago I put together a simple FPV deck using off-the shelf components! The deck simply consists of a camera, VTX and a DC-DC converter, soldered onto a prototype deck.

The deck is very simple and consists of only four components and the price (as of writing) is approximately 50\$ in total.

1. Prototyping deck
2. Camera: RunCam Atom 10x10mm 800TVL FPV Camera
3. VTX: TBS Unify Pro Nano 5G8
4. DC-DC converter: Voltage 5V boost converter (necessary since the camera and the VTX requries 5V.)

I did the wiring as follows:

I soldered the components onto the prototype deck and used some hot glue to attach the camera, as well as on and around the antenna to prevent it from breaking off when crashing. The deck weighs a total of 8.5 grams including connection pins.

I used the newly released upgrade kit on the Crazyflie which made it easier to fly since the motors and propellers makes the drone a lot faster and easier to control flying manually. The upgrade kit also increases the lift capacity of the drone, which is nice so that the extra weight of the camera deck doesn’t become a problem.

When flying FPV race drones you typically want a nice radio controller and there are many options to choose from. I recently got myself a RadioMaster Zorro Radio Controller – 4-in-1 Multi-Protocol which supports a whole variety of different RC protocols, including the popular ones such as frsky, flysky and many more. You can run the popular OpenTX or EdgeTX firmware on it and the controller is equipped with multiple RF chips, whereas one of the chips is the nRF24L01. This means that we can control the Crazyflie with the controller! While I expected several hacks to make this work, thanks to the awesome Bitcraze community someone had already written support for the Crazyflie for the controller.

Below are the steps that I took to control the Crazyflie using a RadioMaster Zorro 4-in-1 controller. In short, we want two different firmwares: 1) Firmware for the remote controller (like the controller OS). 2) Firmware for the internal RF module. Please note that the details of the steps might change in the future, but hopefully it can still be helpful.

2. Clone the repository for the internal RF module: DIY Multiprotocol TX Module.
3. Locate the file Multiprotocol/CFlie_nrf24l01.ino in the repository and set the address of the Crazyflie that you want to connect to in the method CFLIE_initialize_rx_tx_addr().
4. Ensure that the #define CFLIE_NRF24L01_INO is uncommented in the file Multiprotocol/_Config.h
5. Download Arduino IDE in order to build the code for the internal RF module.
6. Open Arduino IDE from the Multiprotocol directory and build the code by Sketch -> Export Compiled Binary. This might take some time since the firmware is quite big. The binary can then be found in Multiprotocol/build/XXX.bin.
7. Plug in the SD card of the remote controller or connect it to the computer using USB-C and start the controller as a storage device.
8. Transfer the two firmware binaries to the firmware directory of the radio controller. Unplug the radio controller and install the EdgeTX/OpenTX binary as the radio firmware, and the Multiprotocol binary for the internal RF module.
9. Create a new model and select the CFLIE protocol.

You should now be ready to fly! So turn on your Crazyflie and ensure that it’s on the address that you assigned in the CFLIE_initialize_rx_tx_addr() method in step 3. The radio should automatically find the correct channel so you shouldn’t have to worry about selecting the right channel.

Conclusions

I think the deck turned out really nice and it’s super cool to fly the Crazyflie in FPV! :) Some notes to consider:

1. It’s possible to fly with the FPV deck with the normal motors and propellers of the Crazyflie but with the thrust upgrade kit the flying is easier and significantly more enjoyable since you can go a lot faster.
2. Ensure that the battery is well and fully charged before flying.
3. There’s no support for On-Screen Display (OSD) on this deck, but it would be a cool thing to test in the future. I believe that most flight controllers that supports onboard OSD has the MAX7456 or AT7456E chip, but there’s probably more ways to do it.
4. The hot glue loosens up slightly from the heat dissipation of the VTX. I added some extra glue and it seems to hold quite well, even after multiple crashes.
5. There are modules that contains the camera and the VTX in the same package, which might be a good/better option for the Crazyflie buying them separately and soldering them together.

Please let me know if you’ve found any mistakes in the text above or if you have any other cool ideas or hacks about FPV for the Crazyflie! :)

Cheers,
Victor

IROS in Kyoto is over and all Bitcrazers are finally back in Sweden again. We had a really good time in Japan and enjoyed all the interesting discussions we had with all of you, thanks!

In this blog post we will describe the demo we were running in the both and talk a bit about all the cool tech that was used. If you want to reproduce it at home or just take a look for inspiration, the code is available on github in the iros-2022 branch of our experimental firmware repo. There is also a page on our web for IROS 2022 with some more information.

The demo has similarities with our previous demo (see IROS 2019) but has been upgraded to be a fully autonomous and decentralized swarm with 9 Crazyflies buzzing around in a cage, going back to charging pads for wireless charging when the battery is running out. The demo supports multiple Crazyflies flying at the same time, avoiding collisions without a central authority, all decision making is done in each Crazyflie, that is fully decentralized.

The hardware is off-the-shelf products available in our store (links here). The software is obviously written specifically for the demo, but we wanted to use the building blocks already available in the system so the demo code is mainly “glue” to connect them together.

## The cage/flying space

The flying space was box shaped, 3×2 meters in foot print and 2.5 meters high. We enclosed it in our lightweight travel cage made from aluminium pipes and a light net. It is a pretty small space to fly multiple Crazyflies in at the same time but it worked! The main problem with such a small space is down-wash from other Crazyflies and having enough room to avoid collisions. 3 Crazyflies worked pretty well, but had the space been larger it would have been possible to fly all nine.

## Localization

Localization was handled by the Lighthouse positioning system. We used two base stations and the lighthouse deck on each Crazyflie which provides the Crazyflies with their current position with high accuracy.

Since the position is computed in the Crazyflie, using only data from on-board sensors, no external communication is needed in relation to the localization system. The only exception was that we uploaded the physical geometry of the system when setting up the cage.

## Path planing

When a Crazyflie is flying in the demo, the standard mode of operation is to fly a randomized pattern of straight lines. From time to time (randomized) the Crazyflie can also chose to fly the spiral that we have used in earlier demos (see the IROS 2019 demo for instance).

When the battery is running out, the Crazyflie goes back to the charging pad for charging. The position is sampled before taking off and this coordinate is used as the landing point to find the charging pad. When landed the Crazyflie verifies that the battery is being charged. If the battery is not charging the Crazyflie assumes it missed the charging pad and it takes off again to adjust the position.

## Charging

The Crazyflies were equiped with the Qi-charging deck for wireless charging. The charging pads are 3D-printed pads with a slope to make the Crazyflie slide into position also if the landing is not perfect. In the center of the pads there are standard Qi-chargers from IKEA mounted to provide power.

To fly continuously, the system charging rate must be higher than what is consumed by the flying Crazyflies. With a system of nine Crazyflies that are charging through Qi-chargers it is possible to keep one Crazyflie flying, just. To get some margin we increased the charging speed a bit, the down side being that the Crazyflies get warm and the batteries ware out faster.

## Collision avoidance

We use the built in collision avoidance system contributed by James Alan Preiss at University of Southern California. Thanks James, it works like a charm!

There is no planing ahead, but each Crazyflie must know where the other Crazyflies are located. Based on this information they avoid each other and chose a new path to reach their target position. For this to work each Crazyflie is continuously broadcasting its position to the other Crazyflies using the peer-to-peer framework.

## Swarm control and collaboration

As mentioned earlier there is no central authority that decides which Crazyflie that should take off or go to a specific position, instead this functionality is handled in each Crazyflie. To make it possible for each Crazyflie to have a rough idea of the system state, each Crazyflie is broadcasting its position and state (landed, flying etc) to the other Crazyflies. If a Crazyflie realizes that too few drones are flying, it will simply take off to fix the problem, if it sees that too many are flying it will go back to the charging pad. To avoid that all Crazyflies takes off or lands at the same time, a randomized hold-back time is used before the actions is executed. This does not fully prevent two individuals from taking off at the same time, but makes it less likely, and eventually the correct number of drones will fly.

The number of drones that should fly at the same time is a system wide parameter that can be set from one of the peers in the system. To make sure they all agree on the value, a simple mechanism is used based on the age of the data. The value and the age of the value is included in the broadcast data. When another Crazyflie receives the data it compares the age of the received data with the age of the data it already has and replaces it only if it is younger.

## Sniffer

A tenth Crazyflie is used in the demo as a sniffer. It is essentially a non-flying member of the swarm that listens to the broadcast traffic and it is used to feed data to a GUI that displays the state of the system. It can also be used to inject a new value for the desired number of flying Crazyflies.

## Implementation and how to run it

The code is mainly implemented as an app in the Crazyflie firmware, using the app layer. The main part is a state machine that keeps track of what to do next with some other modules handling communication and trajectories.

The code is available in the iros-2022 branch of the crazyflie-firmware-experimental repository, in the examples/demos/decentralized_swarm folder.

The examples/demos/decentralized_swarm/src/common_files/choose_app.h file controls if the code is compiled for a swarm member or the sniffer.

All Crazyflies should have the same radio channel and the same address, except the last byte. Swarm members must use addresses ending in 01 to 09 while the sniffer must use the address ending in 00.

The demo is based on the work that Marios did for a decentralized swarm this summer. Thanks Marios!

Since last March, some members of the Bitcraze team went away. Jonas left, and Arnaud took his parental leave. We welcomed an intern, and eventually Arnaud came back but our 6 person team feels a little short.

At Bitcraze, it always seems that there are not enough hours in a day to do everything we want to do. It’s even truer now, when the day-to-day maintenance is longer and it feels like we don’t have the time to dive into our new projects – even though we still manage a lot of new things, like the motor upgrade kit or a conference in Japan.

But if there is not enough man-hour per hour, one solution is simple: hire a new person ! Since this summer, a job post has been up in our webpage. We are officially actively looking for a new teammate !

So, who are we looking for exactly ?

Well, we’re looking for someone that is open, honest, and passionate about technology. That last part is easiest to determine: you must be interested in everything technological, and more specifically embedded systems. At the moment, we’re mostly looking for someone that is interested in the manufacture part of the process, but also in embedded software. However, if you’re a developer with some Python knowledge, and a passion about hardware, you’re might be a right fit as well! Generally speaking, someone with a lots of different interests that would fill the holes we have right now.

And that’s why, frankly, writing a job post is not an easy feat here. In Bitcraze, no one is the manager or “boss”, and we all decide together on what to work on. No one has a definite part, and we talk more easily of passions than fixed role . So, we don’t know exactly now what profile would be the best for us, as it’s more about what you’re willing to do than what you can accomplish. Right now, we’re in need of someone with hardware passion; but maybe we also need someone with a totally different interest that we don’t know about – because we ourselves are not interested in it and didn’t think about it.

The way we work is something that asks for a specific mindset, and we want to make sure that every prospect has the same mentality. Being open-minded, and ready to take on a lot of different tasks and roles, is a very important part of the daily life at Bitcraze, and something we’re searching for in every candidate we meet. And that covers the open and honest part !

In Japan, we came across a shrine dedicated to matchmaking. It is said that the goddess Kuchiire Inari Okami ties together people – whether for marriage or job hires. We made a small offering to her – you never know what can help.

Of course, a more effective way to help us would be to send us your CV at jobs@bitcraze.io and tell us who you are !

By the way, some of us are still in Japan (while the others are recovering from jetlag) so the company might still be running a little slowly this week.

I already talked about it here and there, but this day finally came: the whole company is in Japan !
Kimberly travelled first, to account for jetlag, meet with some people, and attend ROScon.

It was last week, and she got the opportunity to learn a lot, meet people from the ROS community, and give an exciting talk.

The rest of the company travelled last week with all the equipment needed divided into our suitcases.

We chose to rent a traditional machiya while there, where we can all stay together and enjoy the life in the center of Kyoto.

Our first day here was to account for jetlag, but we managed to sightsee the amazing sites of Kyoto – and enjoy the most praised Japanese food, much appreciated after a long walk among the Tori gates of the Fushimi Inari shrine.

But it was soon time to start working, and yesterday we worked really hard on setting up everything to have a nice demo at IROS.

After some head scratching, emergency taping and hacking we managed to get the autonomous demo that Marios implemented last summer flying – just before the event hall We got time to explore the Kyoto International Conference Center, a beautiful venue with a Japanese garden and a futuristic look – as imagined in the 70′.

We invited those of you that are attending IROS to come and see us for a tech meet-up. It’s today and it would be a real nice opportunity for us to finally chat in person with our users ! Since there are a lot of aerial systems talks, we realize it may be difficult to come during the sessions, so the tech meet-up can begin during the break, at 15.40

Next up this week is the safe nanocopter competition. Kimberly will actually deliver the prize for that, we can’t wait to see what this competition will show – and how fun it is to remote-control the Crazyflies that are in the University of Toronto Institute for Aerospace Studies!

Of course, we will share some news on social media – and we will have a blogpost in a few weeks to debrief on the whole trip.

As you’ll understand, maintaining the day-to-day of the company is a little trickier this week, but we still monitor email, github discussions, and are shipping orders. You should just expect a longer time to process those, as we’re too busy – either at the booth or… at karaoke ! (no, there will be no videos of us singing).

As you probably noticed already, this summer I experimented with ROS2 and connecting the Crazyflie with multi-ranger to several mapping and navigation nodes (see this and this blogpost). First I started with an experimental repo on my personal Github account called crazyflie_ros2_experimental, where I managed to do some mapping and navigation already. In August we started porting most of this functionality to the crazyswarm2 project, so that is what this blogpost is mostly about.

## Crazyswarm goes ROS2

Most of you are already familiar with Crazyswarm for ROS1, which is a project that Wolfgang Hönig and James Preiss have maintained since its creation in 2017 at the University of Southern California. Since then, many have used and referred to this work, since the paper has been cited more than 260 times. From all the Crazyflie papers of the latest ICRA and IROS conferences, 50 % of the papers have used Crazyswarm as their communication middleware. If you haven’t heard about Crazyswarm yet, please check-out the nice BAMdays talk Wolfgang gave last year.

Unfortunately, ROS1 will not be there forever and will be phased out anno 2025 and will not be supported for Ubuntu 22.04 and up. Therefore, Wolfgang, now at the Intelligent Multi-robot Coordination Lab at TU Berlin, has already started with the ROS2 port of Crazyswarm, namely Crazyswarm2. Here the same principle of the C++ based Crazyflie server and the python wrapper were been implemented, along with the simple position based simulation and Teleop nodes. Mind that the name Crazyswarm2 is just the project name out of historic reasons, but the package itself can also be used for individual Crazyflies as well. That is why the package names will be called crazyflie_*

## Porting the Summer Hack project to Crazyswarm2

The crazyflie_ros2_experimental was fun to hack around, as it was (as the name suggests) experimental and I didn’t need to worry about releases, bugfixes etc. However, the problem of developing only here, is that the further you go the more work it becomes to make it more official. That is when Wolfgang and I sat down and started talking about porting what I’ve done in the summer into Crazyswarm2. This is also a good opportunity to get more involved with the project, especially with so many Crazyfliers using the ROS as well.

The first step was to write a second crazyflie_server node that relied on the python CFlib. This means that many of the variables I used to hardcode in the experimental node, needed to be defined within the parameter structure of ROS2. The crazyflies.yaml is where anything relevant for the server (like the URIs and parameters) needs to be defined. Both the C++ backend server and the CFlib backend server are using the same parameters. Also the functionality of the both servers are pretty similar, except for that logging is only possible on the CFlib version and uploading/follow trajectories is only possible on the C++ version. An overview will be provided soon on the Crazyswarm2 documentation website.

The second step was to make the crazyflie_server (cflib) node suitable to be connected to external packages that I’ve worked with during the hack project. Therefore, there are some special logging modes, that enables the server to not only output topics based on logging, but Pose/Odometry/LaserScan messages along with Transforms. This allowed the SLAM_toolbox to use the data from the Crazyflie itself to create a map, which you can see an example of in this tutorial.

Moreover, for the navigation it was important that incoming Twist messages either from keyboard or from a navigation toolkit were handled properly. Most of these packages assume a 2D non-holonomic robot, but a quadcopter like the Crazyflie needs to first take off, stay in the air and land. Therefore in the examples, a separate node (vel_mux.py) was written to receive incoming Twist messages, first have the Crazyflie take off in high level commander, and keep sending hover commands to keep it in the air until a land service is called.

## What’s next?

As you probably noticed, the project is still under development, but at least it is now at a good state that we feel comfortable to presented at the upcoming ROScon :) We also want to include an more official simulation package, especially now that the Crazyflie has recently became part of the official release of Webots 2022b, but we are currently waiting on the webots_ros2 to be released in the ubuntu packages. Moreover, the idea is to provide multiple simulation backends that based on the requirement of the topic (swarms, vision-based etc), the user can select the simulation most useful for their situation. Also, we would like to even out the missing items (trajectory handling, logging) in both the cflib and cpp backend of the crazyflie_server so that they can be used interchangeably. Also, I saw that the experimental simple mapper node has been featured on social media, so perhaps we should be converting that to Crazyswarm2 as well :)

So once we got the most of the above mentioned issues out the way, that will be the time that we can start discussing the official release of a ROS2 Crazyflie package with its source code residing in the Crazyswarm2 repository. In the meantime, it would be awesome that anybody that is interested in ROS2, or want to soon upgrade their Crazyswarm(1) packages to ROS2 to give the package a whirl. The more people that are trying it out and report bugs/proposing fixes, the more stable it becomes and closer it will come to an official release! Please join us and start any discussions on the Crazyswarm2 project github repository.

This fall is full of exciting events for us, and none are more excitedly expected than our visit to Japan. Yes, the whole company (6 people) are travelling to Kyoto for at least a week – but not for sightseeing (well, not only). Here is what we have planned:

## ROSCon

As per tradition, ROSCon is held shortly before IROS. So, on the 19 to 21 October, Kimberly will be here to represent us along the ROS community. She will even have a presentation about the latest ROS2 integrations in collaboration with the maintainers of Crazyswarm2. It’s on October 21st, 16.50 local time so if you’re there make sure to hear her talk !

## IROS

From the 21st to the 27th of October, IROS will be held at the Kyoto International Conference Center. it’s one of largest robotics conference worldwide, with almost 1750 papers presented. As the first in-person session of the conference since the beginning of the Covid pandemic, we had to be there. We will man the booth during the whole conference, with the demo our intern Marios has worked on a lot. And since it’s been a long time since we’ve been able to gather and talk together, we thought it would be great to have an official meetup at IROS for those interested.

So, please note this official invitation to Bitcraze’s tech meetup at IROS! If you’re at IROS and want to meet us together with other Crazyflie users, then let’s get together on Monday 24th of October at 16.00 at our booth 59. It’s the perfect occasion to (re)connect, to get the latest news about Bitcraze, to talk about development, share what you’ve been doing and even possibly hack together! Be sure to say hi if you’re there. We will try to make it something similar to a Swedish fika, with some sweets and coffee, but we can’t promise that there will be kanelbullar.

## IROS Safe Robot Learning Competition

And this year, we’re happy to announce that there will be a Crazyflie competition during IROS. The goal is to develop safe learning-based algorithms that can cope with uncertainties not known at design time. Our friends at Dynamic Systems Lab are organizing this competition with two simulated phase, and one experimental phase at IROS… And the experiment is a remote access to the Flight Arena at the University of Toronto Institute for Aerospace Studies in Toronto, Canada via high-speed internet connections. You don’t need to be present at IROS to participate, but if you wish to do so, beware, the registration for the competition ends on October 12th. We’re really curious and excited to see what this competition is going to show!

## What about Bitcraze during that week?

But, if everybody is in Japan, what about Bitcraze’s regular activities ? You may be wondering. Well, no worries. Even though we’re going to be half a world away, the business is going to follow us. Of course, some of us are going to take that opportunity to take some vacations and visit this beautiful country, so during IROS’ week and the week after, the company will run a little bit more slowly than usual. We won’t be as reactive as usual on emails and discussions, but we will still monitor our emails and ship some orders.

Are you planning to visit IROS or ROSCon ? Is there anything in particular in the schedule that you don’t want to miss ? Don’t hesitate to tell us if you want to join the meetup !

Last week we went on a nice trip to Delft, The Netherlands to attend the 22th International Mico Aerial Vehicle Conference and Competition, this time organized by the MAVlab of the TU Delft. Me (Kim), Barbara and Kristoffer went there by train for our CO2 policy, although the Dutch train strikes did made it a bit difficult for us! Luckily we made it all in one piece and we had a great time, so we will tell you about our experiences… with a lot of videos!

## First Conference day

For the conference days we were placed in the main aula building, so that everybody could drop by during the coffee breaks, right next to one of our collaborators, Matěj Karásek from Flapper Drones (also see this blog post)! In the big lecture hall paper talks were going on, along with interesting keynote speeches by Yiannis Aloimonos from University of Maryland and Antonio Franchi from TU Twente.

In between the talks and coffee breaks, we took the opportunity to hack around with tiny demos, for which the IMAV competition is a quite a good opportunity. Here you see a video of 4 Crazyflies flying around a Flapperdrone, all platforms are using the lighthouse positioning system.

The evening of the first day the first competition was planned, namely the nanoquadcopter challenge! In this challenge the goal was to autonomously fly a Crazyflie with an AIdeck and Flowdeck as far as possible through an obstacle field. 8 teams participated, and although most did offboard processing of the AIdeck’s camera streaming, the PULP team (first place) and Equipe Skyrats (3rd place) did all the processing onboard. The most exciting run was by brave CVAR-UPM team that managed to do pass through 4 gates while avoiding obstacles, for which they won a Special Achievement Award.

During the challenge, Barbara also gave a presentation about the Crazyflie while Kristoffer build up the lighthouse positioning system in the background in a record breaking 5 minutes to show a little demo. After the challenge, there were bites and drinks where we can talk with all the teams participating.

Here there is an overview video of the competition. Also there was an excellent stream during the event if you would like to see all the runs in detail + presentations by the teams, you’ll have have a full 3 yours of content, complemented by exciting commentary of Christophe de Wagter and Guido de Croon from the MAVlab. Thanks to all the teams for participating and giving such a nice show :)

## The Green House Challenge

On Wednesday, we were brought to Tomato world, which is a special green house for technology development in horticulture. Here is where the Greenhouse challenge, which was the 2nd indoor drone competition took place. The teams had to participate with their drone of choice to navigate through rows of tomato plants and find the sick variant. Unfortunately we could not be up close and personal as with the nanoquadcopter challenge, but yet again there was a great streaming service available so we were able to follow every step of the way, along with some great presentations by Flapper drones and PATS! drones among others. For the later we were actual challenged to an autonomous drone fight! Their PATS-x system is made and detect pest insects that are harmful for green house crops, so they wanted to see if they can catch a Crazyflie. You can see in the video here that they manage to do that, and although the Crazyflie lived, we are pretty sure that a real fly or moth wouldn’t. Luckily it was a friendly match so we all had fun!

Here is an overview of the Green house challenge. At the end you can also see a special demo by the PULP team successfully trying out their obstacle avoiding Crazyflie in between the tomato plants. Very impressive!

## Last days and final notes

Due to the planned (but later cancelled) train strikes in the Netherlands, the full pack were not able to attend the full event unfortunately. In the end Barbara and I were able to experience the outdoor challenge, where much bigger drones had to carry packages into a large field outdoors. I myself was able to catch the first part of the last conference day, which included a keynote of Richard Bomprey (Royal Veterinary College), whose lab contributed to the mosquito-inspired Crazyflie flight paper published in Science 2 years ago.

We were happy to be at the IMAV this year, which marks as our first conference attendance as Bitcraze after the pandemic. It was quite amazing to see the teams trying to overcome the challenges of these competition, especially with the nanoquadcopter challenge. We would like to thank again Guido de Croon and Christophe de Wagter of the MAVlab for inviting us!

IMAV website: https://2022.imavs.org/

Crazyflie IMAV papers:

• ‘Handling Pitch Variations for Visual Perception in MAVs: Synthetic Augmentation and State Fusion’ Cereda et al. (2022) [pdf]
• ‘Seeing with sound; surface detection and avoidance by sensing self-generated noise‘, Wilshin et al. (2022)

This weeks guest blog post is from Hanna Müller, Vlad Niculescu and Tommaso Polonelli, who are working with Luca Benini at the Integrated Systems Lab and Michele Magno at the Center for Project-Based Learning, both at ETH Zürich. Enjoy!

This blog post will give you some insight into our current work towards autonomous flight on nano-drones using a miniaturized multi-zone depth sensor. Here we will mainly talk about obstacle avoidance, as it is our first building block towards fully autonomous navigation. Who knows, maybe in the future, we will have the honor to write another blog post about localization and mapping ;)

Obstacle avoidance on nano-drones is challenging, as the restricted payload limits on-board sensors and computational power. Most approaches, therefore, use lightweight and ultra-low-power monocular cameras (as the AI-deck) or 1d depth sensors (as the multi-ranger deck). However, both those approaches have drawbacks – the camera images need extensive processing, usually even neural networks to detect obstacles. Neural networks additionally need training data and are prone to fail in completely new scenarios. The 1d depth sensors can reliably detect obstacles in their field of view (FoV); however, no information about the size or exact position of the obstacle is obtained.

On bigger drones, usually lidars or radars are used, but unfortunately, due to the limited weight and power consumption, those cannot be carried and used on nano-drones. However, in 2021 STMicroelectronics introduced a new multi-zone Time-of-Flight (ToF) sensor – with maximal 8×8 pixel resolution, a range up to 4m (according to the datasheet), a small form-factor and low power consumption of only 286mW (typical) it is ideal to use on nano-drones.

In the picture on top, you can see the Crazyflie 2.1 with our custom ToF deck (open-sourced at https://github.com/ETH-PBL/Matrix_ToF_Drones). We described this deck for the first time in [1], together with a sensor characterization. From this, we saw that we could use the sensor in different light conditions and on different colored obstacles, but from 2m on, the measurements started to get incomplete in all scenarios. However, as the sensor can detect invalid measurements (due to interference or obstacles being out of range), we can still rely on our information. In [2], we presented the system and some steps towards obstacle avoidance in a demo abstract, as you can see in the video below:

The next thing we did was to collect a dataset – we flew with different combinations of decks (flow-deck v2, AI-deck, our custom multi-zone ToF deck) and sometimes even tracked by a vicon system. Those recordings amount to an extensive dataset with depth images, RGB images, internal state estimation and the position and attitude ground truth.

We then fed the recorded data into a python simulation to develop an obstacle avoidance algorithm. We focused on only the ToF data (we are not fusing with the camera in this project, we just provide the data for future work). We aimed for a very efficient solution – because we want it to run on-board, on the STM32F405, with low latency and without occupying too many resources. Our algorithm is very lightweight but highly effective – we divide the FoV in different zones, according to how dangerous obstacles in those areas are and then use a decision tree to decide on a steering angle and velocity.

With only using up 0.31% of the computational power and 210 μs latency, we reached our goal of developing an efficient obstacle avoidance algorithm. Our system is also low-power, the power to lift the additional sensor with all accompanying electronics as well as the supply of it totals in less than 10% of the whole drone. On average, our system reaches a flight time of around 7 minutes. We refer to our preprint [3] for details on our various tests – they include flights with distances up to 212 m and 100% reliability and high agility at a low speed in an office environment.

As our paper is currently submitted but not yet accepted our code and dataset are not yet released – however, the hardware design is already accessible: https://github.com/ETH-PBL/Matrix_ToF_Drones

[1] V. Niculescu, H. Müller, I. Ostovar, T. Polonelli, M. Magno and L. Benini, “Towards a Multi-Pixel Time-of-Flight Indoor Navigation System for Nano-Drone Applications,” 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2022, pp. 1-6, doi: 10.1109/I2MTC48687.2022.9806701.
[2] I. Ostovar, V. Niculescu, H. Müller, T. Polonelli, M. Magno and L. Benini, “Demo Abstract: Towards Reliable Obstacle Avoidance for Nano-UAVs,” 2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), 2022, pp. 501-502, doi: 10.1109/IPSN54338.2022.00051.
[3] H.Müller, V. Niculescu, T. Polonelli, M. Magno and L. Benini “Robust and Efficient Depth-based Obstacle Avoidance for Autonomous Miniaturized UAVs”, submitted to IEEE, preprint: https://arxiv.org/abs/2208.12624