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IROS 2022: Crazyflie’s adventures in Robotic Research

  2022-12-05  |     |    Leave a comment

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.

Updates on Simulation work

  2022-03-14  |     |    Leave a comment

In December we had a blogpost where we gave an overview of existing simulation models that were out there. In the mean time, I have done some work during my Fun Fridays to get this to work even further. Currently I moved the efforts from my personal Github repo to the Bitcraze organization github called crazyflie-simulation. It is all still very much work in progress but in this blogpost I will explain the content of the repository and what these elements can already do.

Low Poly CAD model

The first thing that you will need to have for any simulation, is a 3D model of the Crazyflie. There is of course already great models available from the CrazyS project, the sim_cf project and the multi_uav_simulator, which are completely fine to use as well. But since we have direct access to the exact geometries of the real crazyflie itself, I wanted to see if I could abstract the shapes myself. And also I would like to improve my Blender skills, so this seemed to be a nice project to work with! Moreover, it might be handy to have a central place if anybody is looking for a 3D simulation model of the Crazyflie.

For simulations with only one or a few Crazyflie, the higher resolution models from the other repository are absolutely sufficient, especially if you are not using a very complicated physics geometry model (because that is where most of the computation is). But if you would like to simulate very big swarms, then the polygon count will have more influences on the speed of the simulation. So I managed to make it to 1970 vertices with the below Crazyflie model, which is not too bad! I am sure that we can make it even with lesser polygons but this is perhaps a good place to start out with for now.

In the crazyflie-simulation, you can find the Blender, stl files and collada files under the folder ‘meshes’.

Webots model

We implemented the above model in a Webots simulator, which was much easier to implement than I thought! The tutorials they provide are great so I was able to get the model flying within a day or two. By combining the propeller node and rotational motor, and adjusting the thrust and drag coefficient to be a bit more ‘Crazyflie like’, it was able to take off. It would be nice to perhaps base these coefficients on the system identification of the Crazyflie, like what was done for this bachelor thesis, but for now our goal is just to make it fly!

The webots model can found in the same simulation repository under /webots/. You can try out the model by 

webots webots/world/crazyfly_world.wbt

It would then be possible to control the pitch and roll with the arrow keys of your keyboard while it is maintaining a current height of 1 meter. This is current state of the code as of commit 79640a.

Ignition Gazebo model

Ignition will be the replacement for Gazebo Classic, which is already a well known simulator for many of you. Writing controllers and plugins is slightly more challenging as it is only in C++ but it is such a landmark in the world of simulation, it only makes sense that we will try to make a Gazebo model of the Crazyflie as well! In the previous blogpost I mentioned that I already experimented a bit with Ignition Gazebo, as it has the nice multicopter motor model plugin standard within the framework now. Then I tried to make it controllable with the intergrated multicopter velocity control plugin but I wasn’t super successful, probably because I didn’t have the right coefficients and gains! I will rekindle these efforts another time, but if anybody would like to try that out, please do so!

First I made my own controller plugin for the gazebo model, which can be found in the repository in a different branch under /gazebo-ignition/. This controller plugin needs to be built first and it’s bin file added to the path IGN_GAZEBO_SYSTEM_PLUGIN_PATH, and the Crazyflie model in IGN_GAZEBO_RESOURCE_PATH , but then if you try to fly the model with the following:

 ign gazebo crazyflie_world.sdf
Code language: CSS (css)

It will take off and hover nicely. Unfortunately, if you try out the key publisher widget with the arrow keys, you see that the Crazyflie immediately crashes. So there is still something fishy there! Please check out the issue list of the repo to check the state on that.

Controllers

So the reason why I made my own controller plugins for the above mentioned simulation models, is that I want to experiment with a way that we can separate the crazyflie firmware controllers, make a code wrapper for them, and use those controllers directly in the simulator. So this way it will become a hybrid software in the loop without having to compile the entire firmware that contains all kinds of extra things that the simulation probably does not need. We can’t do this hybrid SITL yet, but at least it would be nice to have the elements in place to make it possible.

Currently I’m only experimenting with a simple fixed height and attitude PID controller written in C, and some extra files to make it possible to make a python wrapper for those. The C-controller itself you can try out in Webots as of this commit 79640a, but hopefully we will have the python version of it working too.

What is next?

As you probably noticed, the simulation work are still very much work in process and there is still a lot enhancements to add or fix. Currently this is only done on available Fridays so the progress is not super fast unfortunately, but at least there is one model flying.

Some other elements that we would like to work on:

  • Velocity controller, so that the models are able to react on twist messages.
  • Crazyflie firmware bindings of controllers
  • Better system variables (at least so that the ign gazebo model and the webots model are more similar)
  • CFlib integration
  • Add a multiranger and/or camera.
  • and more!

I might turn a couple of these into topics that would be good for contribution, so that any community members can help out with. Please keep an eye on the issue list, and we are communicating on the Crazyswarm2 Discussion page about simulations if you want to share your thoughts on this as well.

The State of Crazyflie Simulations

  2021-12-13  |     |    8 Comments

I have returned from my family visit in California, who I’ve haven’t seen them in 3 years due to Covid. To spend the most possible time with them, the plan was that I would still work full time for Bitcraze from my father’s home. The problem became however, that it wouldn’t fit so well in our current way of work as I would miss all the morning stand up meetings due to the large time difference between Sweden and California (-9 hours). That is why we settled that I would work on separate projects/investigations during my time away. So I thought it would be a great opportunity to dig into ROS and 3D simulations again and see what the latest state of that is! So about the simulations is what I’ll be mostly talking about right in this blog post, in terms of what simulators are out there and what simulation development is currently ongoing.

Need for simulation?

Why would it be actually be necessary to have a simulation in our current frame work? Just to give an example, my new colleague Jonas recently tried out his hand on the CFlib swarm class for the first time for the BAMdays tutorials, and simulator would have been great during that initial porcess. Namely, most of the crashes were not necessary due to low batteries or bad communication, but mostly due to the fact that he was not able to double check his script beforehand. If one is able to check if all the programmed positions of the Crazyflies are implemented as they should before an actual flight, this would prevented a lot of broken propellers!

Just to note here that there are a lot of types of simulations that you can think of. Earlier this year had our ex-interns Max and Josephine finish an Renode simulation of the Crazyflie’s microcontrollers. We’ve also seen the word Simulink pop-up multiple times on the forum which indicates that quite some control classes are investigating the dynamic model of the Crazyflie. However, the type of simulation that I’m currently referring to are the 3D simulators in which a robot or quadcopter can move and interact with a virtual environment, with usually an physics engine in effect.

Crazyflie in Gazebo (+ROS)

During some initial investigation there were already some simulations that pop out. First of all I went and looked into what is available for Gazebo at the moment, which is:

CrazyS is based on the RotorS simulation with some additional off-board crazyflie controllers for position control. I wasn’t able to build it for my Ubuntu 20.04 just yet myself, but that there is ongoing work to port CrazyS to ROS Noetic. For now on a virtual machine with ROS melodic it build just fine! Note my laptop did had to work quite hard when I wanted to simulate more than 1 Crazyflie, but the physics and plugins that were made for Gazebo is enabling many to do a lot for their research. Please check out the core papers about CrazyS!

Sim_cf is perhaps a little lesser known, but the project does stand out as it has some interesting features to it. It is for instance, possible to use the actual c-based firmware in software-in-the-loop (SITL) mode, which controls the simulated Crazyflie. It is even possible to use an actual crazyflie with an hardware-in-the-loop (HITL) simulation. Eventhough the project is not actively maintained anymore, I did manage to build it from source for ROS Noetic and Gazebo 11, although I was not able to fly more than 4 do to errors.

Other Simulators

Ofcourse Gazebo is not the only possibility out there. I also had a quick go at another simulator called Webots, which is quite an interesting option indeed as well. Currently there is only one quadcopter model available, so it only makes sense for it to also contain an Crazyflie! They do use their own robotic format, so probably the easiest process would be, is to convert an existing model for Gazebo/ROS into an format that Webots can understand.

Also, quite recently, a trending tweet has brought us to the attention of a Rviz based Crazyflie simulation! This looks quite promising as well, so I will try this out quite soon too.

Screenshot from 2021-11-15 11-56-48
Crazyflie in Ignition Gazebo

Ongoing work in Ignition Gazebo

So in the future, the current Gazebo in its form will disappear and will be only be part of Ignition. So that is why it made sense for me to start playing with an separate Crazyflie model and plugins for the Ignition frame work instead. Moreover, it seems that quite some elements and plugins based on the RotorS simulation for the original gazebo, are now fully integrated within the Ignition gazebo framework, which should make it more easier to make quadcopter models fly. Currently it’s still work in progress, so right now is only to be found on my personal github repository, but as soon as it becomes more fleshed out and stable, this will probably transferred to Bitcraze’s github repos and we will write a more elaborate blogpost about it. For now, I’ll try to work on it further as my Fun Friday project!

In the mean time, we have started a simulation discussion thread in the Crazyswarm2 repository, which is an ongoing port of Crazyswarm to ROS2. It would be the ideal situation if we would be able to use this simulator for both Crazyswarm and our native CFlib! But I’ve mostly have used Gazebo in the past, so if there are any other simulators that we should try out too, please join the discussion and let us know!