Category: Lighthouse

As you have noticed, we talk about the lighthouse positioning a lot these last couple of months ever since we got it out of early release. However, it is good to realize that it is not the only option out there for positioning your Crazyflie! That is why in this blog-post we will lay out possible options and explain how they are different/similar to one another.

The four possible ways to position the crazyflie

Absolute Positioning / Off-board Pose Estimation

Absolute Positioning and External Pose Estimation with the MoCap System

The first we will handle are the use of motion capture systems (MoCap), which resolves around the use of InfraRed cameras and Markers. We use the Qualysis camera ourselves but there are also labs out there that use Vicon or Optitrack. The general idea is that the cameras have an IR-light-emitting LED ring, which are bounced back by reflective markers that are supposed to be on the Crazyflie. These markers can therefore be detected by the same cameras, which pass through the marker positions to an external computer. This computer will have a MoCap program running which will turn these detected markers into a Pose estimate, which will in turn be communicated to the Crazyflie by a Crazyradio PA.

Since that the positioning is estimated by an external computer instead of onboard of the crazyflie, a MoCap positioning system is categorized as an off-board pose estimation using an absolute positioning system. For more information, please check the Motion Capture positioning documentation.

Absolute Positioning / On-board Pose Estimation

Absolute Positioning and Internal Pose Estimation with the Lighthouse and Loco Positioning System

The next category is a bit different and it consists of both the Loco positioning system and the Lighthouse positioning system. Even though these both use beacons/sensors that are placed externally of the Crazyflie, the pose estimation is done all on-board in the firmware of the Crazyflie. So there is no computer that is necessary to communicate the position back to the Crazyflie. Remember that you do need to communicate the reference set-points or high level commands if you are not using the App layer.

Of course there are clear differences in the measurement type. A Crazyflie with the Locodeck attached takes the distance to the externally placed nodes as measured by ultra wide band (UWB) and the Lighthouse deck detects the light plane angles emitted by the Lighthouse Base Stations. However the principle is the same that those raw measurements are used as input to the Extended Kalman filter onboard of the Crazyflie, and outputs the estimated pose after fusing with the IMU measurements.

Therefore these systems can be classified as absolute positioning systems with on-board pose estimation. To learn more please read the Loco and Lighthouse positioning system documentation!

Relative Positioning / On-board Pose Estimation

Relative Positioning and Internal Pose Estimation with the Flowdeck V2.

It is not necessary to have to setup an external positioning system in your room in order to achieve a form of positioning on the Crazyflie. With the Flowdeck attached, the Crazyflie can measure flows per frame with an optical flow sensor and the height in millimetres with a time of flight sensor. These measurements are then fused together with the IMU within the Extended Kalman filter (see the Flow deck measurement model), which results in a on-board pose estimation.

The most important difference here to note is that positioning estimated by only the Flowdeck, will not result in a absolute positioning estimate but a relative one. Instead of using an external placed system (like MoCap, Lighthouse and Loco) which dictate where the zero position is in XYZ, the start-up position the Crazyflie determines where the origin of the coordinate system is. That is why the Flowdeck is classified as a Relative Positioning System with On-board Pose Estimation.

IMU-only On-board Pose Estimation ?

Oh boy… that is a different story. Theoretically it could be possible by using the onboard accelerometers of the crazyflie and fusing those in some short of estimator, however practice has shown that the Crazyflie’s accelerometers are too noisy to result in any good pose estimation… We haven’t seen any work that has been successfully to achieve any stable hover on only the IMU of the Crazyflie, but if you have done/see research that has, please let us know!

And if you would like to give a go yourself and build an estimator that is able to do this, please check out the new out of tree build functionality for estimators. This is still work in progress so it might have some bugs, but it should enable you to plugin in your own estimator separate from the Crazyflie firmware ;)

Documentation

We try to keep keep all the information of all our positioning systems on our website. So check out the positioning system overview page to be referred to more details if you would be interested in a particular system that fits your requirements!

Now that the Lighthouse deck is out of early access and we have made it easier to setup a lighthouse positioning system, we are currently at the next stage: showing how awesome it is! We feel that there are not enough people out there that know about the Lighthouse positioning system and sometimes confuse it even with the Loco position system (to be honest, the abbreviation LPS makes it challenging). But we are confident that the Lighthouse system is a good alternative for those that want to do drone research but are on a tight budget.

The area of the data collection. from the paper

Lighthouse Dataset

During Wolfgang Hönig‘s time here at Bitcraze, one of the bigger projects we worked together on was to generate a dataset comparing the positioning quality of the Lighthouse system with a Motion Capture (MoCap) system. You could imagine that would be a difficult task, since as the lighthouse basestations transmit infrared light sweeps and MoCap cameras by default also emit IR light which are reflected back by markers. However, with the Active marker deck for the Qualysis system, we were able to use the MoCap and Lighthouse positioning without too much interference.

Moreover, Wolfgang also helped out with improving the logging quality on the Micro-SD-card deck which also enabled us to get as much data real-time as possible. He wrote a blogpost about event-based logging a few weeks ago which is a new approach to record data on the Crazyflie at a fast pace. With the Active Marker Deck, the Micro-SD-card deck and of course the Lighthouse deck, … the Crazyflie turn into a full-blown positioning data-collection machine!

The configuration of the Crazyflie with the Micro-SD-card deck, the Lighthouse-deck from the lighthouse dataset paper

Paper

About this whole process, we wrote the following paper:
Lighthouse Positioning System: Dataset, Accuracy, and Precision for UAV Research,
A.Taffanel, B. Rousselot, J. Danielsson, K. McGuire, K. Richardsson, M. Eliasson, T. Antonsson, W. Hönig, ICRA Workshop on Robot Swarms in the Real World, Arxiv 2021

This paper contains an short explanation of the lighthouse system, how we set up the data collection and an analysis of the results, where we compared both Lighthouse V1 and V2 with the Crossing beam (C.B.) method and the extended Kalman filter. In all cases, the mean and median Euclidean error of the Lighthouse positioning system are about 2-4 centimeters compared to our MoCap system as ground truth.

Check out the lighthouse dataset paper to read all the details of the experiments!

The Euclidean Error of both LH1 and LH2 with Mocap as ground-truth taken from the dataset paper.

ICRA Swarm Workshop

Our paper is selected for a poster presentation at the ICRA 2021 Workshop: Robot Swarms in the Real World. So if you have any questions about the paper, please join and ask us in person! The workshop will be held on the 4th of June.

Moreover, we also are sponsoring the event by giving away a Lighthouse Swarm Bundle to whomever wins the best video-demonstration award! So to all the participants, the best of luck! We are super curious to what you’ll have to show us.

A few weeks ago we released version 2021-03 including the python library, Cfclient and the firmware. The biggest feature of that release was that we (finally) got the lighthouse positioning system out of early access and added it as an official product to the Crazyflie eco system! Of course we are very excited about that milestone, but the work does not end there… We also need to communicate how to use it, features and where to find all this new information to you – our favourite users!

New Landing Page

First of all, we made a new landing page for only the lighthouse system (similar to bitcraze.io/start) we now also have bitcraze.io/lighthouse. This landing page is what will be printed on the Lighthouse base station box that will be available soon in our store, but is also directly accessible from the front page under ‘Product News’.

This landing page has all kinds of handy links which directs the user to the getting started tutorial, the shop page or to its place within the different positioning systems we offer/support. It is meant to give a very generic first overview of the system without being overloaded right off the bat and we hope that the information funnel will be more smooth with this landing page.

New tutorial and product pages

For getting started with the lighthouse positioning system, we heavily advise everybody to follow the new getting started tutorial page, even if you have used the lighthouse system since it’s early access days. The thing is is that the procedure of setting the system up has changed drastically. The calibration data and geometry are now stored in persistent memory on-board the Crazyflie and the lighthouse deck itself is now properly flashed. So if you are still using custom config.mk, hardcode geometry in the app layer or use get_bs_geometry.py to get the geometry… stop what you are doing and update the crazyflie firmware, install the newest Cfclient, and follow the tutorial!

We also already made some product page for the Lighthouse Swarm bundle. Currently it is still noted as coming soon but you can already sign up to get a notification when it is out, which we hope to have ready in about 1-2 month(s). The lighthouse deck was of course already available for those that can not wait and want to buy a SteamVR base station somewhere else. Just keep in mind that, even though the v1 is supported, in the future we will mostly focus on the version 2 of the base stations.

Video tutorial

Once again we have ventured into the land of videos and recorded a “Getting started with the Lighthouse positioning system” tutorial for those who prefer video over text.

Feedback

We love feedback and want to improve! Please don’t hesitate to contact us on contact@bitcraze.io if you have comments or suggestions!

We are happy to anounce the availability of the 2021.03 release of the Crazyflie firmware and client! This release includes new binaries for the Crazyflie (2021.03), the Crazyflie client 2021.03 as well as the Crazyflie python library 0.1.13.2. The firmware package can be downloaded from the Crazyflie release repository (2021.03) or can be flashed directly using the client bootloader window. The firmware package contains the STM firmware (2021.03), the NRF firmware (2021.03) and the Lighthouse deck FPGA binary (V6).

The main feature in this release is the stabilization of the Lighthouse positioning system. The main work done has been on the system setup and management, it has taken a lot of work spawning all the projects and a brunch of documentation, but we think we have reached a stage where the lighthouse positioning system is working very well and is very easy to setup and get working. We have now published the new Lighthouse getting started guide and will be working this week at updating all required materials to mark Lighthouse as released!

When the Lighthouse positioning system was released in early access, it required to install SteamVR, run some custom scripts and flash a modified firmware to get up and running. This has been improved slightly over time with scripts that allows to setup the system without using SteamVR and some way to store the required system data in the Crazyflie configuration memory rather than hard-coded in the firmware. With this release, everything is coming together and it is now possible to go from zero to an autonomous Crazyflie flying in a lighthouse system in minutes by just using the Crazyflie client.

Another major improvement made to support the lighthouse is the modification of the bootloader Crazyflie update sequence in the client as well as in command line. The new sequence will restart the Crazyflie a couple of times while upgrading the Crazyflie, this allows for an upgrade of the firmware in the installed decks if required. The lighthouse deck firmware has been added to the Crazyflie .zip release file and will be flashed into the deck while flashing the release to a Crazyflie that has the deck installed.

An alternative, robust TDoA implementation has been added for the Loco Positioning System. This change has been contributed by williamwenda on Github and can optionally be enabled at runtime.

An event subsystem has also been added to the firmware. It allows to log events onto the SD-Card which can be very useful when acquiring positioning data from the various positioning system supported by the Crazyflie. We have described this subsystem in an earlier blog post.

There has also been a lot of smaller improvement and bugfixes in this release. See the individual project releases not for more information.

We hope you are going to enjoy this new Crazyflie and lighthouse release. Do not hesitate to drop a comment here, questions on the forum if you have any or bug reports of github in the (very unlikely ;-) event that there are bugs left.

One crucial aspect of any research and development is to record and analyze data, which then can be used for quantifying performance, debugging strange behavior, or guide us in our decision making. We have been trying to improve the way that this is done to help all of you researcher out there with their work, so this blog post will explain an alternative, better, method to record whatever is happening on the Crazyflie in real-time.

Example data collection of received Lighthouse angles over time. The y-axis contains a unique measurement ID (16 in total for 4 sensors * 2 basestations * 2 sweeps/basestation). Thus, each dot represents the time when a certain kind of measurement was received. We do not receive all angles in fixed intervals, because of the interference between basestations.

Existing Logging Approaches

So far there have been two principle ways of recording data with the Crazyflie:

  1. Logging: In the firmware, one can define global variables that can be streamed out at a fixed frequency, using logging configurations. Variables have a name and data type, and the list of all available variables can be queried from the firmware.
  2. Debug Prints: It is possible to add DEBUG_PRINT(…) in any place that contains a string and possibly some variables. These are asynchronous, but not timestamped, so they are mostly useful to notify the user of some status change.

Both approaches have multiple backends. The logging variables can be streamed over USB, via the Crazyradio, or on a Micro-SD-card using a specialized deck. When using the radio or USB, the frequency is limited to 100 Hz and only a few variables can be streamed at this speed due to bandwidth limitations. The Micro-SD-card deck, on the other hand, allows to log a lot more logging variables at speeds up to 1 kHz, making it possible to access high-speed sensor information, e.g., the IMU data. The Debug Prints can be used over the radio or USB, or with a SEGGER J-Link and a Debug Adapter, over J-Link Real-Time Transfer (RTT). The former is very bandwidth limited, while the latter requires a physical wire connection, making it impossible to use while flying.

New Approach: Event-Based Logging

Event-based logging combines the advantages of the existing approaches and offers a third alternative to record data. Similar to debug prints, a user can trigger an event anywhere in the code and include some mandatory variables that describe this event (so-called payload). Similar to logging, these events are timestamped and have fewer bandwidth limitations. Currently, there is just one backend for the Micro-SD-card deck, but it would be possible to add support for radio and USB as well.

One of our first test cases of the event-based logging is to analyze the data we get from the Lighthouse deck. Here, we trigger an event whenever we received a raw sweep. This allows us to visually see the interference that happens between two LH2 basestations. We also use the event-based logging for time synchronization of the Crazyflie and a motion capture system: when we enable the IR LEDs on the active marker deck, we record an event that contains the Crazyflie timestamp. On the PC side, we record a PC timestamp when the motion capture system first detects the IR LEDs. Clock drifts can be computed by using the same logging mechanism when the IR LEDs are turned off.

Adding event-based logging had some other good side effects as well: the logging is now generally much faster, there is more user feedback about the correct buffer size usage, and the binary files are smaller. More details are in the documentation.

Future Work

We are working on adding event triggers to the state estimator. This will enable us to record all the sensor information during real flights with different positioning systems, so that we can tune and improve the Kalman state estimator. It will also be interesting to add support for events in CRTP, so that it can be used over USB and radio.

We’re happy to announce the availability of the 2021.01 release! The release includes the Crazyflie firmware (2021.01), the python library (0.1.13.1) and the python client (2021.1). The firmware package can be downloaded from the Crazyflie release repository (2021.01) or can be flashed directly using the client bootloader window.

Most of the improvements have been done in the Crazyflie firmware and include:

The App API in the Crazyflie firmware has been extended and improved to be able to handle a wider range of applications. The goal is to enable a majority of users to implement the functionality they need in an app instead of hacking into the firmware it self.

We have improved the Lighthouse support in the firmware and both V1 and V2 are now working well. Even-though everything is not finished yet, we have taken a good step towards official Lighthouse positioning.

A collision avoidance module has kindly been contributed by the Crazyswarm team.

A persistant storage module has been added to enable data to be persisted and available after the Crazyflie is power cycled. It will initially be used to store Lighthouse system information, but will be useful for many other tasks in the future.

Basic arming functionality has been added for platforms using brushless motors.

In the client the LPS tab now has a 3D visualization of the positioning system and a new tab has been added to show the python log output.

Unfortunately we have run into some problems for the Windows client build which is not available for this release.

Finally we have fixed bugs and worked to improve the general stability.

We hope you enjoy it!

Storage is one of these very simple functionality that actually ends up being quite hard to implement properly. It is also one of these functionality that is never acutely needed, it is possible to hack around it, so it gets pushed to be implemented later. Later is now, we have now implemented a generic persistent storage subsystem in the Crazyflie.

In Crazyflie 1.0, we originally stored settings in a setting block in flash and required the bootloader to change the settings. When designing Crazyflie 2.0 we added an I2C EEPROM to make it easier to store settings, though until now we only stored a fix config block very similar to the one stored in the Crazyflie 1 and that only contained basic radio settings and tuning. This implementation is hard to evolve since the data structure is fixed in one point of the code.

What is now implemented is a generic key-buffer database stored in the I2C EEPROM. From the API user point of view, it is now possible to store, retrieve and delete a buffer using a string as a key. This allows any subsystem, or apps, in the Crazyflie to easily store and retrieve their own config blocks. There is 7KB of space available for storage in the EEPROM.

The first user of this new storage subsystem is the Lighthouse driver. The storage is used to store lighthouse basestation geometries and calibration data, this allows to configure a Crazyflie for a system/lab and have it running out of the box even after a restart.

A future use-case would be to implement stored-parameters: we have been thinking about implementing optional persistence for the parameters for a long time. This would allow to modify and then store new default values for any parameters already present in the Crazyflie. This would allow to very easily implement things like custom controller tuning in a quad made from a bolt for example.

At low level, we where hopping to be able to find a ready-to-use library or file system to store data in our small EEPROM, but unfortunately we did not find anything that would fit our needs. We then had to implement our own storage format.

The low level structure is documented in the Crazyflie firmware repos. Basically the data are stored as a table of “length-key-value” entries with a possibility for an entry to he a “hole”. When new buffers are added they are added at the end of the table and when they are deleted they are replaced by a hole. When the end of the table is reached, the table is de-fragmented by removing the holes and moving the data as much as possible to the beginning of the memory. This structure works very well for an EEPROM and could even be adapted to work well on FLASH.

New CI

When we started activating continuous integration/automatic build to our GitHub repos we did so using Travis CI for firmware builds and AppVeyor for windows builds. However, the GitHub CI offering, GitHub actions, has become quite complete lately and now supports Linux, Windows as well as MacOS builds.

We have now transitioned to GitHub actions for all our repos and we will also implement most of the release process using GitHub actions as well. This will hopefully streamline the release process and allow us to release new version of our projects more often.

With the raging pandemic in the world, 2021 will most likely not be an ordinary year. Not that any year in the Bitcraze universe has been boring and without excitement so far, but it is unusually hard to make predictions about 2021. Any how, we will try to outline what we see in the crystal ball for the coming year.

Products

What products are cooking in the Bitcraze pot and what tasty new gadgets can we look forward to this year?

Lighthouse

We did hope that we would be able to release the first official version of the Lighthouse system in 2020, but unfortunately we did not make it. It has turned out to be more complex than anticipated but we do think we are fairly close now and that it will be finished soonish, including support for lighthouse V2.

Once the official version has been achieved, we are planning to assemble an full lighthouse bundle, which includes everything you need to start flying in the lighthouse positioning system. This will also include the Basestations V2 as developed by Valve corporation, so stay tuned!

New platforms and improvements

We released the AI-deck last year in early release, but the AIdeck will be soon upgraded with the latest version of the GAP8 chip. For most users this will not change much but for those that really push the deep learning to the edge will be quite happy with this improvement. More over, we are planning to by standard equipped the gray-scale camera instead of the RGB Bayer filter version, due to feedback of the community. We are still planning to offer the color camera on the side as a separate product for those that do value the color information for their application.

Also we noticed the released of several upgraded versions of sensors for the decks that we already are offering today. Pixart and ST have released a new TOF and motion sensor so we will start experimenting with those soon which hopefully lead to a new Multiranger or Flowdeck. Also we are aware of the new DWM3000 chip which would be a nice upgrade to the LPS system, so we will start exploring that as well, however we are not sure if we will be able to release the new version of LPS in 2021 already.

One of the field that we have wanted to improve for a while but have not gotten to so far is the communication with the Crazyflie. The Crazyradio is using a quite old chip and the communication protocol has hardly been touched in years. There now exists a much more powerful nRF52 radio chip with USB port so it can give us the opportunity to make a new Crazyradio and, at the same time, rework the communication protocols to make them more reliable, easier to use and to expand.

People and Collaborations

Last year we have started several collaborations with show drone orientated business, which we are definitely moving forward with in 2021. For shows stability and performance is very important so with the feedback of those that work with that on a regular basis will be crucial for the further development and reliability of our products.

Moreover we would like to continue our close collaboration with researchers at institutes and universities, to help them out with achieving their goals and contribute their work to our opensource firmware and software. Here we want to encourage the community to make their contributions easy to use by others, therefore increasing the reproducibility of the implementations, which is a crucial aspect of research. Also we are planning to have more of our online tutorial like the one we had in November.

We also will be working with closely together with one of our very active community members, Wolfgang Hönig! He has done a lot of great work for the Crazyswarm project from his time at University of Southern California (USC) and has spend the last few years at Caltech. He will be working together with us for a couple of months in the spring so we will be very happy to have him. Moreover, we will also have 2 master students from LTH working with us on the topic hardware simulation in the spring. We are making sure that we can all work together in the current situation, either sparsely at the office or fully online.

In 2021, we will also keep our eyes open for new potential Bitcrazers! We believe that everybody can add her/his own unique addition to the team and therefore it is important for us to keep growing and get new/fresh ideas or approaches to our problem. Usually we would meet new people at conferences but we will try new virtual ways to get to know our community and hopefully will meet somebody that can enhance our crazy group.

Working from home

Due to the pandemic we are currently mainly working from home and from the looks of it, this will continue a while. Even though we think we have managed to find a way to work remotely that is fairly efficient, it is still not at the same level as meeting in real-life, so there is always room for improvement. Further more the lack of access to electronics lab, flight lab and other facilities when working from home, does not speed work up. We will try to do our best though under the current circumstances and are looking forward to an awesome 2021!

It’s that time of the year again ! As the days get darker and darker here in Sweden, we’re happy to getting some time off to share some warmth with our families.

And to kick off the holiday season, we prepared a little treat for you ! We enjoyed making a Christmas video that tested how we could use the Crazyflie at home. Since we’re not at the office anymore, we decided to fly in our homes and this video shows the different ways to do so. First, take a look at what we’ve done:

Now let’s dig into the different techniques we used.

  • Tobias decided to fly the Bolt manually. His first choice was to land in the Christmas sock, but that was too hard, thereof the hard landing in top of the tree. We were not sure who would survive: the tree or the Bolt!
  • Kimberly installed two base stations V2’s and after setting up, determined some way points by holding the Crazyflie in her hand. Then she generated a trajectory with the uav_trajectories project (like in the hyper demo). Then she used the cflib to upload this trajectory and make the crazyflie fly all the way to the basket. Her two cats could have looked more impressed, though!
  • Using trials and errors, Barbara used the Flowdeck, the motion commander, and a broken measuring tape to calibrate the Crazyflie’s path next to the tree.
  • Arnaud realized that, with all the autonomous work, we hardly fly the Crazyflie manually anymore. So he flew the Crazyflie manually. It required a bit more training that expected, but Crazyflie is really a fun (and safe!) quad to fly.
  • Marcus used two Lighthouse V2 base stations together with the Lighthouse deck and LED-ring deck. For the flying, he used the high level commander. The original plan was to fly around his gingerbread house, but unfortunately it was demolished before he got the chance (by some hungry elves surely!)
  • Kristoffer made his own tree ornament with the drone, which turned out to be a nice addition to a Christmas tree !

It was a fun way to use our own product, and to show off our decorated houses.

I hope you enjoy watching this video as much as we enjoyed making it.

We are staying open during the Holiday season but on a limited capacity: we still ship your orders, and will keep an eye on our emails and the forum, but things will get a bit slower here.

We wish you happy holidays and safe moments together with your loved ones.

This autumn when we had our quarterly planing meeting, it was obvious that there would not be any conferences this year like other years. This meant we would not meet you, our users and hear about your interesting projects, but also that we would not be forced to create a demo. Sometimes we joke that we are working with Demo Driven Development and that is what is pushing us forward, even-though it is not completely true it is a strong driver. We decided to create a demo in our office and share it online instead, we hope you enjoy it!

The wish list for the demo was long but we decided that we wanted to use multiple positioning technologies, multiple platforms and multiple drones in a swarm. The idea was also to let the needs of the demo drive development of other technologies as well as stabilize existing functionality by “eating our own dogfood”. As a result of the work we have for instance:

  • improved the app layer in the Crazyflie
  • Lighthouse V2 support, including basic support for 2+ base stations
  • better support for mixed positioning systems

First of all, let’s check out the video

We are using our office for the demo and the Crazyflies are essentially flying a fixed trajectory from our meeting room, through the office and kitchen to finally land in the Arena. The Crazyflies are autonomous from the moment they take off and there is no communication with any external computer after that, all positioning is done on-board.

Implementation

The demo is mainly implemented in the Crazyflie as an app with a simple python script on an external machine to start it all. The app is identical in all the Crazyflies so the script tells them where to land and checks that all Crazyflies has found their position before they are started. Finally it tells them to take off one by one with a fixed delay in-between.

The Crazyflie app

When the Crazyflie boots up, the app is started and the first thing it does is to prepare by defining a trajectory in the High Level Commander as well as setting data for the Lighthouse base stations in the system. The app uses a couple of parameters for communication and at this point it is waiting for one of the parameters to be set by the python script.

When the parameter is set, the app uses the High Level Commander to take off and fly to the start point of the trajectory. At the starting point, it kicks off the trajectory and while the High Level Commander handles the flying, the app goes to sleep. When reaching the end of the trajectory, the app once more goes into action and directs the Crazyflie to land at a position set through parameters during the initialization phase.

We used a feature of the High Level Commander that is maybe not that well known but can be very useful to make the motion fluid. When the High Level Commander does a go_to for instance, it plans a trajectory from its current position/velocity/acceleration to the target position in one smooth motion. This can be used when transitioning from a go_to into a trajectory (or from go_to to go_to) by starting the trajectory a little bit too early and thus never stop at the end of the go_to, but “slide” directly into the trajectory. The same technique is used at the end of the trajectory to get out of the way faster to avoid being hit by the next Crazyflie in the swarm.

The trajectory

The main part of the flight is one trajectory handled by the High Level Commander. It is generated using the uav_trajectories project from whoenig. We defined a number of points we wanted the trajectory to pass through and the software generates a list of polynomials that can be used by the High Level Commander. The generated trajectory is passing through the points but as a part of the optimization process it also chooses some (unexpected) curves, but that could be fixed with some tweaking.

The trajectory is defined using absolute positions in a global coordinate system that spans the office.

Positioning

We used three different positioning systems for the demo: the Lighthouse (V2), the Loco Positioning system (TDoA3) and the Flow deck. Different areas of the flight space is covered by different system, either individually or overlapping. All decks are active all the time and pick up data when it is available, pushing it into the extended Kalman estimator.

In the meeting room, where we started, we used two Lighthouse V2 base stations which gave us a very precise position estimate (including yaw) and a good start. When the Crazyflies moved out into the office, they only relied on the Flowdeck and that worked fine even-though the errors potentially builds up over time.

When the Crazyflies turned around the corner into the hallway towards the kitchen, we saw that the errors some times were too large, either the position or yaw was off which caused the Crazyflies to hit a wall. To fix that, we added 4 LPS nodes in the hallway and this solved the problem. Note that all the 4 anchors are on the ground and that it is not enough to give the Crazyflie a good 3D position, but the distance sensor on the Flow deck provides Z-information and the overall result is good.

The corner when going from the kitchen into the Arena is pretty tight and again the build up of errors made it problematic to rely on the Flow deck only, so we added a lighthouse base station for extra help.

Finally, in the first part of the Arena, the LPS system has full 3D coverage and together with the Flow deck it is smooth sailing. About half way the Crazyflies started to pick up the Lighthouse system as well and we are now using data from all three systems at the same time.

Obviously we were using more than 2 basestations with the Lighthouse system and even though it is not officially supported, it worked with some care and manual labor. The geometry data was for instance manually tweaked to fit the global coordinate system.

The wall between the kitchen and the Arena is very thick and it is unlikely that UWB can go through it, but we still got LPS data from the Arena anchors occasionally. Our interpretation is that it must have been packets bouncing on the walls into the kitchen. The stray packets were picked up by the Crazyflies but since the Lighthouse base station provided a strong information source, the LPS packets did not cause any problems.

Firmware modifications

The firmware is essentially the stock crazyflie-firmware from Github, however we did make a few alterations though:

  • The maximum velocity of the PID controller was increased to make it possible to fly a bit faster and create a nicer demo.
  • The number of lighthouse base stations was increased
  • The PID controller was tweaked for the Bolt

You can find the source code for the demo on github. The important stuff is in examples/demos/hyperdemo

The hardware

In the demo we used 5 x Crazyflie 2.1 and 1 x Bolt very similar to the Li-Ion Bolt we built recently. The difference is that this version used a 2-cell Li-Po and lower KV motors but the Li-Ion Bolt would have worked just as well.

Hyperdemo drones and they configurations

To make all positioning to work at the same time we needed to add 3 decks, Lighthouse, Flow v2 and Loco-deck. On the Crazyflie 2.1 this fits if the extra long pin-headers are used and the Lighthouse is mounted on top and the Loco-deck underneath the Crazyflie 2.1 with the Flow v2 on the bottom. The same goes for the Bolt, but here we had to solder the extra long pin-header and the long pin-header together to make them long enough.

There is one catch though… the pin resources for the decks collide. With some patching of the loco-deck this can be mitigated by moving its IRQ to IO_2 using the solder-jumper. The RST needs to be moved to IO_4 which requires a small patch wire.

Also some FW configuration is needed which is added to the hyperdemo makefile:

CFLAGS += -DLOCODECK_USE_ALT_PINS
CFLAGS += -DLOCODECK_ALT_PIN_RESET=DECK_GPIO_IO4

The final weight for the Crazyflie 2.1 is on the heavy side and we quickly discover that fully charged batteries should be used or else the crash probability is increased a lot.

Conclusions

We’re happy we were able to set this demo up and that it was fairly straight forward. The whole setup of it was done in one or two days. The App layer is quite useful and we tend to use it quite often when trying out ideas, which we interpret as a good sign :-)

We are satisfied with the results and hope it will inspire some of you out there to push the limits even further!