Author: Kimberly McGuire

Announcement: We will have a townhall meeting this Wednesday (7th of December) about Crazyradio 2.0 and the ideas about the new com-stack at 15:00 (3 pm) CET. Please follow the discussion here for more info.

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.

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.

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 Nanoquadcopter challenge

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 overview video
The full stream of the nanoquadcopter challenge

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!

PATS versus Crazyflie battle

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)

There are some nice and exciting improvement in the CF-client that we worked on during the summer months! First of all we worked on a toolbox structure, where every tab can be reconfigured as a toolbox as well, allowing it to be docked to the sides of the window. Secondly we have added a new geometry estimation wizard for Lighthouse systems to support multi base-station estimation. Finally we have added a new tab for PID controller tuning, mainly intended for the Bolt.

New tabs, toolboxes and wizards for the CFclient

Toolboxes in the CFclient

Everyone who used the CFclient has experienced the tabs before. Anytime you want to configure the lighthouse system, setup plotting or look at the parameter states, you switch to the appropriate tab to perform your desired action. This is all fine, but sometimes it can be useful to see the contents of two tabs at the same time, maybe you want to watch the graphing of a log variable at the same time as you change a parameter. This is what the combined tab/toolbox feature adds! Any tab can now be converted into a toolbox that can be docked to the side of the window.

Plotter tab with parameter toolbox

In the example above the plotter is displaying the estimated position of a Crazyflie with a Flow deck, while the parameter window is opened as a toolbox. The “motion.disable” parameter was just set to true and we can see that the kalman estimator gets into trouble when it no longer gets data from the flow deck.

To switch from tab to toolbox mode, go to the View/Toolboxes menu and select the window that you want to show as a toolbox. In a similar way, use the View/Tabs menu to turn it back to a tab.

Even though all tabs can be turned into toolboxes, some of them might still look better as tabs due to their design. We hope to be able to improve the design over time and make them more toolbox friendly, contributions are welcome!

Lighthouse Geometry Estimation Wizard

In a blogpost of almost a half year ago, we presented a new multi base station geometry estimation method that enabled the user to include more than 2 base station for flying a Crazyflie. This heavily increases the flight area covered by the base station V2s, as technically it should be able to handle up to 16!

New geometry estimation dialog

However, up until this summer it has been in experimental mode as we weren’t so sure as how stable this new estimation method is, so the only way to use it was via a script in the Crazyflie python library directly, and not from the CFclient. Since we haven’t heard of anybody having problems with this new experimental feature, we decided to go ahead to make a nice multi base station geometry estimation wizard in the CFclient’s Lighthouse tab.

This wizard can be accessed if you go to the lighthouse tab-> ‘manage geometry’ and press ‘Estimate Geometry’. We had to make it a wizard as this new method requires some extra intermediate steps compared to the previous, to ensure proper scaling, ground plane setting and sweep angle recording. If you are only using 2 base stations this seems like extra effort, where you only had to put the Crazyflie on the ground and push a button, but if you compare flight performance of the two methods, you will see an immediate difference in positioning quality, especially around the edges of your flight area. So it is definitely worth it!

First page of the wizard

We will still provide the “simple” option for those that want to use it, or want to geometry estimate only one base-station, as we don’t have support for that for this new estimator (see this issue). In that case, you will have to install the headless version of opencv separately like ‘pip3 install opencv-python-headless’. We will remove this requirement from the cflib itself for the next release as there are conflicts for users who has installed the non-headless opencv on their system, like for the opencv-viewer of the AI-deck’s wifi streamer for instance.

PID tuning tab

The PID controller tuning tab

And last but not least, we introduced an PID tuning tab in a PR in the CFClient! And of course… also available as a toolbox :) This is maybe not super necessary for the Crazyflie itself, but for anyone working with a custom frame with the Bolt or BigQuad deck this is quite useful. Tuning is much handier with a slider than to adjust each parameter numerically with the parameter tab. Also if you are just interested of what would happen if you would increase the proportional gain of the z-position controller of the crazyflie, this would be fun to try as well… but of course at your own risk!

If you are happy with your tuned PID values, there is the “Persist Values” button which will store the parameters in the EEPROM memory of the Crazyflie/Bolt, which means that these values will persist even after restarting the platform. This can be cleared with the ‘Clear persisted values’ button and you can retrieve the original firmware-hardcoded default values with ‘Default Values’ button. Please check out this blogpost to learn more about persistent parameters.

Try it out for yourself!

This client has not been released yet but you can already go ahead and try these new features out for yourself. Make sure to first install the client from source, and then install the CFlib from source, as an update of both is necessary. Also update the crazyflie-firmware to the latest development branch via these instructions, especially if you want to try out the new LH geometry wizard.

And of course, don’t forget to give us feedback on discussions.bitcraze.io or to make an issue on the cfclient, cflib or crazyflie-firmware github repositories if you are hitting a bug on your machine and you know pretty precisely where it comes from.

Now it is time to give a little update about the ongoing ROS2 related projects. About a month ago we gave you an heads-up about the Summer ROS2 project I was working on, and even though the end goal hasn’t been reached yet, enough has happened in the mean time to write a blogpost about it!

Crazyflie Navigation

Last time showed mostly mapping of a single room, so currently I’m trying to map a bigger portion of the office. This was initially more difficult then initially anticipated, since it worked quite well in simulation, but in real life the multi-ranger deck saw obstacles that weren’t there. Later we found out that was due to this year old issue of the multi-ranger’s driver incapability to handle out-of-range measurements properly (see this ongoing PR). With that, larger scale mapping starts to become possible, which you can see here with the simple mapper node:

If you look at the video until the end, you can notice that the map starts to diverge a bit since the position + orientation is solely based on the flow deck and gyroscopes , which is a big reason to get the SLAM toolbox to work with the multi-ranger. However, it is difficult to combine it with such a sparse ‘Lidar’ , so while that still requires some tuning, I’ve taken this opportunity to see how far I get with the non-slam mapping and the NAV2 package!

As you see from the video, the Crazyflie until the second hallway. Afterwards it was commanded to fly back based on a NAV2 waypoint in RViz2. In the beginning it seemed to do quite well, but around the door of the last room, the Crazyflie got into a bit of trouble. The doorway entrance is already as small as it is, and around that moment is also when the mapping started to diverge, the new map covered the old map, blocking the original pathway back into the room. But still, it came pretty close!

The diverging of the map is currently the blocker for larger office navigation, so it would be nice to get some better localization to work so that the map is not constantly changed due to the divergence of position estimates, but I’m pretty hopeful I’ll be able to figure that out in the next few weeks.

Crazyflie ROS2 node with CrazySwarm2

Based on the poll we set out in the last blogpost, it seemed that many of you were mostly positive for work towards a ROS2 node for the Crazyflie! As some of you know, the Crazyswarm project, that many of you already use for your research, is currently being ported to ROS2 with efforts of Wolfgang Hönig’s IMRCLab with the Crazyswarm2 project. Instead of in parallel creating separate ROS2 nodes and just to add to the confusion for the community, we have decided with Wolfgang to place all of the ROS2 related development into Crazyswarm2. The name of the project will be the same out of historical reasons, but since this is meant to be the standard Crazyflie ROS2 package, the names of each nodes will be more generic upon official release in the future.

To this end, we’ve pushed a cflib python version of the crazyflie ros2 node called crazyflie_server_py, a bit based on my hackish efforts of the crazyflie_ros2_experimental version, such that the users will have a choice of which communication backend to use for the Crazyflie. For now the node simply creates services for each individual Crazyflie and the entire swarm for take_off, land and go_to commands. Next up are logging and parameter handling, positioning support and broadcasting implementation for the CFlib, so please keep an eye on this ticket to see the process.

So hopefully, once the summer project has been completed, I can start porting the navigation capabilities into the the Crazyswarm2 repository with a nice tutorial :)

ROScon talk

As mentioned in a previous blogpost, we’ll actually be talking about the Crazyflie ROS2 efforts at ROScon 2022 in Kyoto in collaboration with Wolfgang. You can find the talk here in the ROScon program, so hopefully I’ll see you at the talk or the week after at IROS!

In the first years that I started at Bitcraze I’ve been focused mostly on embedded development and algorithmic design like the app layer, controllers and estimators and such, however recently I started to be quite interested in the robotic integration between the Crazyflie and other (open-source) projects and users. This means that I’ll be dwelling more often in the space between Bitcraze and the community, which is something that I do really enjoy I noticed during the Grand Tour. It also initiated my work with simulators which I think would be very useful for the community too. The summer fun project that I’ve been now working on is to integrate the Crazyflie with ROS2 to integrate standard navigational packages, which will be the topic of this blogpost!

ROS2 Crazyflie Node

So first I worked on the ROS2 node that actually communicates with the Crazyflie directly. I think many of you are familiar with the USC’s CrazySwarm project, of which the ROS2 variant, CrazySwarm2, is already available for most functionalities. Even though the name says CrazySwarm, this can be very easily used for only one Crazyflie too. The CrazySwam2 is currently under more development by the IMRClab of TU Berlin, but please take a look if you want to give it a go!

For now while Crazyswarm2 is still under development, I used the Bitcraze Crazyflie python library to make a more hackish node that just publishes exactly the information I want. I am focusing on the scenario with the STEM ranging bundle, aka the Crazyflie + Flowdeck (optical flow + distance sensor) + Multi-ranger (5 x distance sensors) combo, where the node logs the multi-ranger data and the odometry from the Flowdeck with the Crazyradio and outputs that into necessary /scan and /odom topics. Moreover, it also outputs several tf2 transforms that makes it possible to either visualize it in RVIZ and/or connect it to any other packages and it should react to incoming twist messages as well.

Development with a Simulator

And of course… I went in head first and connected it directly with the SLAM toolbox. I have worked with ROS1 in the past, but I had my first experience working with that package in the course: Build Mobile Robots with ROS2 (by Weekly Robotic Newsletter’s Mat Sadowski), so I couldn’t wait to try it on a real platform like the Crazyflie. However, tuning this was of course more work than I thought, as the map that I got out of it first was mostly a sparse collection of dots. Of course the SLAM toolbox is meant for lidars and not something that provided sparse range distances like the Multiranger. Then I decided to take one or two steps back, and first connect a simulator to make tuning a bit easier.

Luckily, I’ve already started to look at simulators, and was quite far in the Webots integration of the Crazyflie. Actually… Webots’ next release (2022b) will contain a Crazyflie as standard! Once it is out, I’ll write a blogpost about that separately :). As luck has it, Webots also has good ROS2 integration as well, and even won the ‘Best ROS Software’ award by The Construct’s ROS awards! Another reason is that I wanted to try out a different simulator for ROS2 this time to complement what I’ve learned in the ROS2 course I mentioned earlier.

So I used the webots driver node to write a simulated Crazyflie that should output the same information as the real Crazyflie node, so that I can easily hack around and try out different things without constantly disturbing my cats from their slumber :). Anyway, I won’t go into to the simulator too much and save that for another blogpost!

Simple Mapping

I decided to also take another additional step before going full SLAM, which is to make a simple mapper node first! This takes the estimated state estimate of the Crazyflie and the Multiranger’s range values and it creates an occupancy grid type map of it. I do have to give kudos to the Marcus’ cflib Pointcloud script and Webot’s simple mapper example, as I did look at them for some reference. But still with the examples, integration and connecting the dots together is quite some work. Luckily I had the simulator to try things out with!

So first I put the Crazyflie in an apartment simulator, flew around and see if any decent maps comes out of it and it seemed it did! Of course, the simulated Crazyflie’s ‘odometry’ comes from near perfect position estimate, so I didn’t expect any problems there (and in such a situation you would actually not really need the localization part of SLAM). This still needs some improvements to be done, like now range measurements that don’t see anything are excluded from drawing, but still it was pretty cool to map the virtual environment.

So it was off to try it out on a real crazyflie. In one of our meeting rooms, I had one Crazyflie take off, let it turn around with a twist message in a /cmd_vel topic and made a map of the room I was currently in. The effect of the 4 range sensors rotating around and creating a map in one go, makes me think of these retro video transitions. And the odometry drift does not seem as bad for it to be possible, but I haven’t mapped our entire office yet so that might be different!

What’s next?

So I’m not stopping here for sure, I want to extend this functionality further and for sure get it to work with the SLAM_toolbox properly! But if the simple mapper already can produce such quality, I’m pretty sure that this can be done in one way or the other. What I could also do, is first generate a simple map and already have a go at the NAV2 package with that one… there are many roads to Rome here!

Currently I’m doing my work on my personal Github account in the crazyflie_ros2_experimental repository. Everything is still very much in development, hackish and quite specific for one use case but that is expected to change once things are working better, so please check the planning in the project’s readme. In the mean time, you can indicate to us in this vote if this is an interesting direction for us to go towards. Not that it will stop me from continuing this project since it is too much fun, but it is always good to know if certain efforts are appreciated!

Earlier this month, ICRA 2022 was in held in Philadelphia and in person this time! Unfortunately we were unable to attend ourselves but quite happy that there were still virtual attendance options available. So I followed quite some presentations and read through papers, trying to find out the latest in Aerial and Swarm robotics and if anybody was able to use the Crazyflie to good use for their research. I even had the opportunity to attend the Exhibition floor with a telepresence robot, which was a lot of fun!

We have covered IROS 2021 end of last year, and we even have started to publish Crazyflie related publications on social media to keep ourselves and the community up to date with any Crazyflie research work. So here we will list the ICRA 2022 papers we have found and write some observations.

Crazy Platforms

What I really noticed this year is that the Crazyflie has been used in more unconventional configurations and new platforms! IROS 2021 ready amazed us by a solar-powered Crazyflie and the 4 times Crazyflie combined quadcopter (which continued this conference by UCLA in (2). But we haven’t seen yet that a Crazyflie can jump! The PogoDrone by the Swarmslab of Lehigh university turned the Crazyflie into an autonomous jumping pogo stick (5)! Moreover, wheels were added by the Institute For Systems and Robotics (TU Lisbon) for increasing the flight/autonomy durability (7).

We also noticed 3 ICRA 2022 papers with Bolt-powered platforms, which is a huge increase compared to IROS 2021 which only had 1 Bolt entry. The MAVlab of the TU Delft compared the Crazyflie against a Bolt-powered Flapper-drone for flying against wind (see the presentation of Flapperdrone in our last MiniBam). Moreover, remember that saw the Science Robotics paper using a Crazyflie board for a dual wing rotating platform. The Engineering product development of SUTD took a similar design to the next level, building a single controllable rotating wing with a Bolt platform (3). Two of these can even work together cooperatively and fly stability, so it is no wonder that they won the ICRA 2022 Outstanding Dynamics and Control Paper Award.

List of ICRA 2022 Papers featuring the Crazyflie and Bolt

Here is a list of all the Crazyflie/Bolt papers featured in ICRA 2022 but let us know if we are missing any (⚡: Bolt, 🐝: Crazyflie). Mind that only Robotic and Automation Letter entries have been officially published on IEEE Xplore already, so from the proceeding papers I tried to share the ArXiv paper if available.

  1. ⚡ ‘Passive Wall Tracking for a Rotorcraft with Tilted and Ducted Propellers using Proximity Effects’ Ding et al. from City University of Hong Kong & Massachusetts Institute of Technology
  2. 🐝 ‘A Fast and Efficient Attitude Control Algorithm of a Tilt-Rotor Aerial Platform Using Inputs Redundancies’ Su et al. from UCLA
  3. ⚡x2 ‘Cooperative Modular Single Actuator Monocopters Capable of Controlled Passive Separation’, Cai et al. from Singapore University of Technology & Design
  4. 🐝’Optimal Inverted Landing in a Small Aerial Robot with Varied Approach Velocities and Landing Gear Designs’ Habas et al. from Penn State
  5. 🐝 ‘PogoDrone: Design, Model, and Control of a Jumping Quadrotor’, Zhu et al from Lehigh U.
  6. 🐝 ‘Clustering and Informative Path Planning for 3D Gas Distribution Mapping: Algorithms and Performance Evaluation’, Ercolani et al from EPFL
  7. 🐝 ‘A Bimodal Rolling-Flying Robot for Micro Level Inspection of Flat and Inclined Surfaces’ , Pimentel et al from Instituto Superior Tecnico
  8. 🐝x 2 ‘Collision Avoidance for Multiple Quadrotors Using Elastic Safety Clearance Based Model Predictive Control’, Jin et al. from USTC & Sina
  9. 🐝 + ⚡🦋 ‘An Experimental Study of Wind Resistance and Power Consumption in MAVs with a Low-Speed Multi-Fan Wind System’, Olejnik et al. from TU Delft
  10. 🐝x 6 ‘Formation-containment tracking and scaling for multiple quadcopters with an application to choke-point navigation’, Su et al. from The University of Manchester.

Updated

11. 🐝x 6 ‘Nearest-Neighbor-Based Collision Avoidance for Quadrotors Via Reinforcement Learning’, Ourari et al. from TU Darmstadt
ArXiv

12. 🐝x 6 ‘Safe multi-agent motion planning via filtered reinforcement learning’ Vinod et al. from Mitsubishi Electric Research Laboratories
IEEEXplore page

13. 🐝 ‘Event-Triggered Tracking Control Scheme for Quadrotors with External Disturbances: Theory and Validations’, Goa et al. from University of Shanghai for Science and Technology
Outstanding Coordination / Mechanisms & Design / Locomotion / Navigation Award Finalists
IEEEXPlore page

14. 🐝 ‘Watch and Learn: Learning to control feedback linearizable systems from expert demonstrations’, Sultangazin et al. from University of California
IEEEXplore page
15. ‘KoopNet: Joint Learning of Koopman Bilinear Models and Function Dictionaries with Application to Quadrotor Trajectory Tracking’, Folkestad et al. from Caltech
IEEEXplore page

Other Announcements: Bolt 1.1 and Dev meeting

Bolt 1.1

The Bolt is now back in stock and with two small updates making it the Bolt 1.1. Here are the changes listed:

  1. The board thickness has been reduced from 1.6mm to 1.0mm to save some weight, roughly 2 grams. This is handy for the slimmest and most lightweight designs.
  2. Motor signal output M4 has been moved from PB9 to PB10 to be able to support the DSHOT motor signal protocol in the future.

Other then that it is fully backwards compatible but make sure to use a recent enough firmware (2022.03) that has the Bolt 1.1 device support added.

Time and Date for Dev Meeting

In this blogpost we noted that we wanted to organize our first Developer meeting before the summer break. From this poll we saw that most of you that want to attend are currently located in Asia and Australia, so that is why this time we want to organize the meeting at:

13:00 CEST (Sweden time) on Wednesday 22th of June.

The topic will be about our new support platform and support handling in general, so I’m hoping for some fruitful discussions about that. Keep an eye on this discussion thread for any details for joining.

We have already announced it a bit on social media, but in this blogpost we are announcing it officially: we are moving our support to Github Discussions which can be reached by going to discussions.bitcraze.io. We will deprecate our old forum and lock it for new thread creation and user registration starting from week of the 6th of June.

Don’t worry! We don’t have any plans of removing the actual content of the old forum as this is much too valuable for support. But for most communication, support and discussions, we will only be using Github Discussions.

The Reasoning

Technically, there is nothing really wrong with the old forum! Bitcraze has used this phpBB-based platform ever since 2013 and has helped tremendously in support in all those years until now. For a long while, it also has been an active sharing medium next to support, where users could share their cool Crazyflie projects. So it was more than a support channel… it was a community watering-hole! Unfortunately, the backbone of the forum has not progressed in functionality, the categories style defeated it’s purpose and we found we had to constantly switch back and forth between the forum and Github issue list on a daily basis. So we have decided it is time for something else.

Moreover, the last few years we have noticed that the sharing of cool projects became significantly less, no more discussions were initiated and the forum was mostly used for only support and questions. As we missed seeing cool projects and discussing the Crazyflie (also due to Corona), we tried to open up a Bitcraze Discord channel (see this blogpost) to initiate more discussions and sharing as a supplement to the forum. Unfortunately, it did not really take off in terms of activity, and the content is not searchable without a discord account. After a unfortunate hack-attack last year we removed the invite link from our website.

We did get feedback that having 2 platforms separated for support and community was confusing to the users, as they didn’t know where to ask a question anymore. The ideal situation would then to be choose another platform where we can have all on there. Discourse we had our eyes on for a while, which has been used by other open source projects, and has integration support for Github so users didn’t have to make yet another account. Github itself introduced their Discussions feature 1.5 year ago and it was adopted by Crazyswarm (1 and 2). At that time it was only possible to have one discussion tab per repository, and with our 60 (!) repos this didn’t seem to be an option… until recently! Once they released their organization level discussion feature about a 1.5 months ago, we were sold. There is no better Github integration than being on Github itself and with our many repos, this is something we definitely need.

How to use Discussions?

The forum and discussions are quite different in style which takes a little getting used to. The old forum used a classic ‘thread’, which shows exactly the chronological way of the conversation. Discussions uses an approach similar to Stack Overflow, where you can also reply on intermediate answers in that thread.

Where to start a discussion?

If you see the discussion page, you notice a couple of categories. These are still the standards as given by github, but we think these will work for us as well:

  • Announcements: Here is where Bitcraze places announcements in regards of discussions. You can not add announcements yourself but you can reply to them, but do not start a generic support question here.
  • General: Just for generic discussions and saying hi!
  • Ideas: If you have any ideas for enhancements for the Bitcraze ecosystem, place them here!
  • Polls: Same as announcements from Bitcraze, but we will use these to poll a certain opinion.
  • Q&A: Here is were all the support questions go! Make sure to read the support rules for this.
  • Show & Tell: Show your awesome Crazyflie projects here!

Labels

We first had categories at the forum, which was supposed to separate the discussion in a functional way. In reality, sometimes it was difficult to really separate the issues in those very categories as it overlapped many functionalities. Now in Github discussions, we are able to label these based on the topic, and even add more labels if it indeed overlaps multiple topics. From this, we will also be able to filter out support question about a certain topic which will make it easier for us to have a good look of all support for a certain product or functionality.

So please try to label your support question! But if you haven’t, we will probably do it for you.

Issue or Discussion?

Especially since we are on Github discussions, it might be difficult now to determine when to start an issue at an individual repository and when to start discussion. I really like the explanation that Github itself used to explain the difference:

Discussions are great for questions and ideas that require team communication to make a decision, while Issues are defined pieces of work.

So if you know of a bug/problem, or you want to to propose an enhancement that you know the specific repository of, go ahead and make an issue right in that repo. If you have a problem and you are not sure what is causing it, discussions is the place to go (preferably in Q&A). If there is any ‘pieces of work’ that comes from that discussion, the maintainer can generate an issue in the related repository and link it to the discussion. Other way around, any questions in any issue list that we think is too generic, we will moderate and move it to the organization discussions.

Get involved!

Of course at Bitcraze we will try to help out, but what we really would like is for you to help with answering questions as well! Start up and chat with a topic that you are interested in, or show a small video of your Crazyflie doing something fun. One thing that we would love is the community to be as vibrant as it used to be, were we not only ask support questions, but to discuss and share! It doesn’t have to be big, like you can vote on this Poll to voice your opinion about our move, or vote up / add a smiley to any discussion that you find important.

Also we are planning to have a developer meeting in a few weeks, on the 22nd of June (just before the holidays), so please see the discussion/poll here for more information.

We have worked hard last week to get a new fresh release out before the summer months are on our doorstep. Not only that we would like to make sure that important bugs are fixed before some of us go on our holiday, but also to be able to display our new AI deck features! Here is an overview of what has been changed

AI deck over air flashing

As you can probably see in the release notes of both the python libraries and the firmware, most of our changes are focused on making it possible to develop for the AI deck without using a programmer all the time. If the STM and NRF firmware of the Crazyflie is fully updated, and the ESP firmware on the AI deck, it should now be possible to flash an AI deck example binary with a Crazyradio! For older versions of the AI deck 1.X (Rev A to C) it is unfortunately still necessary to use the JTAG programmer one last time to flash a bootloader on the GAP8, but after that it should not be needed anymore.

Please check out the new update AI deck tutorial for setting up the AI deck for this new functionality.

Crazyflie Packet eXchange (CPX)

In the light of the work we have done for the AI deck, we also have started to implement a new, inter MCU protocol called the Crazyflie Packet Exchange. Since with the AI deck, we are adding 2 additional microprocessors to the Crazyflie architecture, it was crucial to handle the communication between all platforms and communication channels properly. Currently the functionality is mostly enabled to tailor Wifi streaming and console printouts for the AI deck, but it is meant to be a generic protocol which in the future, should be able to handle more combinations like for instance, command messages through wifi?

You can read about CPX in the crazyflie-firmware repository doc and we will be writing a more detailed blogpost about this later.

Controller Python bindings

For the last part of the Grand tour trip, we had a hackathon with the IMRC lab of TU Berlin and our close collaborator Wolfgang Hönig, in which we managed to convert the PID controller, Mellinger controller and the motor mixing into python bindings, which can be used in the experimental simulator of the Crazyflie.

There is no Pypi release of these, you will need to pull the latest crazyflie-firmware repo and build the bindings with ‘make bindings_python’

Additional fixes

We have some additional fixes to both the python libraries and firmware. For the STM we have updated the STD peripheral library and solved several build issues. For the cfclient, we fixed a lot of issues that were caused by either the latest version of python, as it was more stricter with type definitions, and some issues QT. Moreover, the LED ring headlight functionality has been restored, and the cfbridge.py script, used for the PX4 crazyflie 2.1 tutorial, is re-added, since it suddenly disappeared a few releases ago.

Update and Feedback

Make sure to update your cfclient with ‘pip install cfclient –upgrade’ and to reflash the new stable firmware. For AI deck users, try out our our new tutorial to try out both CPX, the over air flashing and the wifi example. The new AI deck functionalities has been subjected to some limited testing so if there is anything wrong or unclear, please let us know in the forum! The feedback will help the AI deck to become a more stable product for development, so we would be very grateful if you would be able to help out with that.

If anybody noticed a delay of my response on emails, forum or Github, that might be due to the fact that I was on the road for Bitcraze for the last few weeks! I was invited to give a guest lecture for a course at EPFL, and of recent they have a CO2 reducing policy regarding travel. At Bitcraze we also aim for reducing our environmental impact, so hence the idea came forth to travel to Switzerland and visit our close collaborators that are nearby(ish)… all by train! Internally we dubbed this to be The Grand Tour.

The Itinerary

We kept the itinerary mostly within Switzerland and Germany, although I did pass the Netherlands a few days just to visit family. The full itinerary by train was:

Utrecht (NL) -> Lausanne (SW) -> Zürich (SW) -> Munich (GE) -> Berlin (GE) -> Malmö (SE)

The longest train ride was from Utrecht to Lausanne (9 hours), but all the others were well under 4 hours which was pretty comfortable. The nice thing about being in the train is that it quite easy to work on your laptop (although the wireless network + onboard WiFi was still patchy). Luckily I was able to actually phone in for Bitcraze’s morning meetings so that I wouldn’t miss a thing.

Here are some pictures of the in-between travels, with the views, trains and food. It was all awesome, but if I do have to make a confession… the train rides through Switzerland was the most beautiful of all!

Travelling through Switzerland and Germany

The People

The first two days in Lausanne went quite smoothly. Dario Floreano of the Laboratory of Intelligent Systems (LIS) invited us to give a Crazyflie 101 lecture to the students of the Aerial Robotics course, for which we are very grateful for the opportunity. It was great to do the talk in person this time and visit the EPFL campus, since the last two years I’ve given the same lecture from my own kitchen. I was able to see the students trying to start up the course themselves, and actually got to experience how they would install the Crazyflie framework. Next to my lecture, I was given a very nice tour through the offices, laboratories and work-spaces, where I had the possibility see all the nature inspired drone designs of the LIS-lab. In the meantime I also squeezed in a quick but fun visit with Cyberbotics, the creator of Webots, to discuss our latest efforts for a crazyflie simulator.

After a beautiful train ride towards Zurich, I first met up with the people of the Automatic Control lab (ACL), who made a video about how they handled education with the Crazyflie during the harsher COVID times. Now I got a chance to see the flight room where students are able control their Crazyflie down to the rate attitude controller. Moreover, I was treated to a full workshop, hosted by ETH Zürich’s Integrated Systems Lab (IIS) and Center of Project Based learning (PBL), joined by researchers from ETHZ, University of Bologna and IDSIA (Lugano) working on the PULP platform and/or nano-drones. The workshop consisted of them and us showcasing our current work, future plans and they showed me very impressive demos with both the AIdeck and their own prototypes decks! Complete that with a lunch with one of the best views any campus has to offer, coffee break talks, and you have a very inspiring day.

The third part of the trip took place in Germany! My first stop was near Munich, namely Hochschule Augsburg, where I visited the Cooperative Control Lab lead by Klaus Kefferpütz where we had great discussions about collaborative swarms and state estimators. They showed their lab with demos, and we spoke about positioning systems and how to improve their development experience. They are currently integrating the Bolt with a Raspberry Pi with the latest functionalities we implemented into our firmware, which we can imagine is a very wanted feature by the community! I also had a brief visit at TU Munich as well to visit my friend Sophie Armanini from the eAviation and Sustainable Flight Group, and to my surprise I got to fly with a Crazyflie Bolt fueled Flapper drone!

As my final stop, I visited Wolfgang Hönig from the Intelligent Multi-Robot Coordination Lab (IMRC) at TU Berlin. Here we discussed all about Crazyswarm, simulations and firmware python bindings among many things. Also, we had a successful hackathon where we managed to generate python bindings of the Mellinger & PID controller and the motor mixing. On top of that, we managed to fly with the PID binding in the Webots simulator, which has been on the wish list for a little while now. It was great working together again in person after 1.5 years!

Collection of the tours, the platforms and the people I’ve met!

The Insights

It was great to see all the different ways that our products are used and what matters to the community members were dealing with. I’ve visited labs that tweak the attitude rate controllers, trying to improve the quality of the state estimators, or experiment with the actual mechanics. However, it was clear to see that quite some were controlling the Crazyflies on a higher level of autonomy, either off-board or onboard. This is all spread out over education and research alike, so there is a very wide range of people that are working with the Crazyflie.

There is of course also a huge variety in their approach. Some used our internally development framework with the Cflib and cfclient, and I’ve generated quite some new Github tickets in those respective repositories based on the discussions I had. However, it was interesting to see that many have made their own clients to tailor more to their research and education objectives. Moreover, about half of the users I met used ROS to interact with the Crazyflies. Is it perhaps a sign that we should start to rethink the communication infrastructure and how it all fits together?

There was also quite the difference on how close these users were on our latest changes. It ranged from working on a branch forked 4 years ago to being on the very edge of the commits, which each have their pros and cons. Working on a stable branch that has been proven worthy might be beneficial with education classes, but also makes people miss out on new features like the new lighthouse integration. However, it is not all fine and dandy on the edge of development either, as I have heard of many having issues with the new kbuild intergration, installing the cfclient or our latest efforts of getting the AIdeck out of early access. That is something that these pioneers has to deal every time they merge the new master, so we need to find better ways to make it easier for them as well.

And last but not least, it seems that the simulation we have been working on has generated quite the buzz, as most of whom I spoke to were quite interested in it, or has used a different simulation for their purpose. It was clear that there is not yet a standard simulator for aerial robotics that can fulfill everybody’s requirements in terms of swarming, (vision-based) autonomy or control. Perhaps that is a good reason to promote the simulation work from Fun-Fridays to a regular day project and have some interesting future discussions with the community how to shape this to most of our needs.

The Conclusion

All and all, those were very inspiring 2 weeks of travel for me. Even though physically I was a bit exhausted afterwards, mentally it was very motivating and inspiring! After two of the worst years of the pandemic it was great to talk to people in person and I really feel stronger connections with those I visited than the remote video calls we have done before. It is so important to stay in touch with the community in person, after so long time of absence, as we get a better sense of what the needs are and how people are using the Crazyflie and its ecosystem. The Grand Tour was according to us a great success, and who knows…. perhaps we will do an 2023 edition as well :)