Safety and the Brushless

2023-04-24 | Kimberly McGuire | 1 Comment

It is easy to forget that the reason why it is nice to develop for the Crazyflie is because it weighs only about 30 grams. In case something goes wrong with your script or there is a fly-away, you can simply pick it up from the air without worrying about the propellers hitting you. Moreover, when the Crazyflie crashes, it usually only requires a brush off and a potential replacement of a motor-mount or propeller. The risk of damage to yourself, other people, indoor furniture, or the vehicle itself is extremely low. However, things become very different if you’ve built a larger platform with the Bolt or BQ deck with large brushless motors (like with this blogpost), where the risk of injury to people or to the vehicle itself increases significantly. That is one of the major reasons why the BQ deck and the Bolt are still in early access and have been for a while. In our efforts to get it out of early access, it’s time to start thinking about safety features.

In this blog post, we’ll be discussing how other open-source autopilot programs are implementing safety features, followed by a discussion on current efforts for Crazyflie, along with an announcement of the developer meeting scheduled for May 3rd (see below for more info).

Safety in other Autopilots

We are a bit late to the game in terms of safety compared to other autopilot programs such as PX4, ArduPilot, Betaflight and Paparazzi UAV, which have been thinking about safety for quite some time. It makes a lot of sense when you consider the types of platforms that run these autopilots, such as large fixed VTOL or fixed-wing vehicles or 10-kilo quadcopters with cinematic cameras, or the degree of outdoor flight regulation. Flying a UAV autonomously or by yourself has become much more challenging as the US, EU, and many other countries have made it more restrictive. In most cases, you are not even allowed to fly if fail-safes are not implemented, such as what to do if your vehicle loses GPS signal. These types of measures can be separated into pre-flight checks and during-flight checks.

Pre-flight checks

Before a vehicle is allowed to fly, or even before the motors are allowed to spin, which is called ‘arming’, several conditions must be met. First, it needs to be checked if all internal sensors, such as the IMU, barometer, and magnetometer, are calibrated and functional, so they don’t give values outside of their normal operating range. Then, the vehicle must receive a GPS signal, and the internal state estimator (usually an extended Kalman filter) should converge to a position based on that information. It should also be determined if an external remote control is connecting to the vehicle and if there is any datalink to a ground station for telemetry. Feasibility checks can also be implemented, such as ensuring that the mission loaded to the UAV is not outside its mission parameters or that the start location is not too far away from its take-off position (assuming the EKF is functional). Additionally, the battery should not be low, and the vehicle should not still be in an error state from a previous flight or crash.

All of these features have the potential to be turned off or made less restrictive, depending on your situation. However, keep in mind that changing any of these may require recertification of the drone or make it fall outside what is required for outdoor flight regulation. Therefore, these should only be changed if you know what you are doing.

Preflight checks documentation

PX4: https://docs.px4.io/main/en/flying/pre_flight_checks.html#preflight-sensor-estimator-checks
ArduPilot: https://ardupilot.org/copter/docs/common-prearm-safety-checks.html#failure-messages
Beta flight: https://betaflight.com/docs/wiki/archive/GPS-Rescue-v4-4#sanity-check-options
Paparazzi UAV: Indicated per platform if necessary, on their wiki: https://wiki.paparazziuav.org/wiki/Failsafe

Fail-safe triggers during flight

Now that the pre-flight checks have passed, the UAV is armed and you have given it the takeoff command. However, there is so much more that can go wrong during a UAV flight, and takeoff is one of the most dangerous moments where everything could go wrong. Therefore, there are many more safety features, aka failsafes, during the flight than for the pre-flight checks. These can also be separated into ‘triggers’ and ‘behaviors,’ so that the developer can choose what the UAV should do in case of a failure, such as ‘GPS loss’ to ‘land safely’ and so on.

Thus, there are triggers that can enable the autopilot’s failsafe mechanics:

No connection with the remote control
No connection with the Ground station or Datalink
Low Battery
Position estimate diverges or full GPS loss
Waypoint going beyond geofence or Mission is not feasible
Other vehicles are nearby.

Also, sometimes the support of an external Automatic Trigger system is required, which is a box that monitors the conditions where the UAV should take action in case there is no GPS, other aerial vehicles are nearby, or the UAV is crossing a geofence determined by outdoor flight restrictions. Note that all of these triggers usually have a couple of conditions attached, such as the level of the ‘low battery’ or the number of seconds of ‘GPS loss’ deemed acceptable.

Fail-safe behavior

If any of the conditions mentioned above are triggered, most autopilot suites have some failsafe behaviors linked to those set by default. These behaviors can include the following:

No action at all
Warning on the console or remote control display
Continue the mission autonomously
Stay still at the same position or go to a home position
Fly to a lower altitude
Land based on position or safely land by reducing thrust
No input to motors or completely disarming the motors

Usually, these actions are set in regulation, but per trigger, it is possible to give a different behavior than the default. One can decide to completely disarm the vehicle, but then the chances of the UAV crashing are pretty high, which can result in damage to the vehicle or cause harm to people or objects. By the way: disarming is the opposite act of arming, which is not allowing the motors to spin, no matter if it is receiving an input. If you decide to never do anything and force the drone to finish the mission autonomously, then in a case of GPS or position loss, you risk losing your vehicle or that it will end up in areas where it is absolutely not allowed, such as airports. Again, changing these default behaviors should be done by someone who knows what they are doing, and it should be done with careful consideration.

Failsafe documentation other autopilot suites:

PX4: https://docs.px4.io/main/en/config/safety.html
ArduPilot: https://ardupilot.org/copter/docs/failsafe-landing-page.html
Betaflight: https://betaflight.com/docs/development/Failsafe
Paparazzi UAV: https://wiki.paparazziuav.org/wiki/Failsafe

Emergencies

Fail-safes are measures that ensure safe flight. However, there will always be a chance that an emergency will occur, which will require an immediate action as well. If the vehicle has crashed during any of its phases or has flipped, or if the hardware breaks, such as the motors, arms, or perhaps even the autopilot board itself, what should be done then?

The standard default behavior for this is to completely disarm the vehicle so that it won’t react to any input to the motors itself. Of course, it’s difficult to do if the autopilot program is on, but at least it won’t try to take off and finish its mission while laying on its side. It might be that a backup system is connected to the ESCs that will take over in case the autopilot is not responding anymore, perhaps using a different channel of communication.

Also, the most important safety feature of all is the pilot itself. Each remote control should have a special button or switch that can put the drone in a different mode, make it land, or disarm it so that the pilot can act upon what they see. In case the motors are still spinning, have a net or towel available to throw over them, disconnect the battery as soon as possible, and make sure to have sand or a special fire retardant in case the LiPo batteries are pierced.

All of the autopilots have some tips to deal with such situations, but make sure to do some good research yourself on how to handle spinning parts or potential LiPo battery fires. I’m just giving a compilation of tips given in the documentation above here, but please make sure to read up in detail!

Safety in the Crazyflie Firmware

So how about the Crazyflie-firmware ? We have some safety features build in here and there but it is all over the code base. Since the Crazyflie is so safe, there was no immediate need for this and we felt it is more up to the developer to integrate it themselves. But with the Bolt and BQ deck coming out of early access, we want to at least do something. As we started already started looking into how other autopilot softwares are doing it, we can get some ideas, however we did notice that many of these are mostly meant for outdoor flight. The Crazyflie and the Crazyflie Bolt have been designed for indoor use and perhaps deal with different issues as well.

Current safety features

This is a collection of safety features currently in the firmware at the time of writing this blogpost. Most safety features in the Crazyflie are up for the developer to double check before and during flight, but these are some automatic once that are scattered around the firmware:

Preflight testing of different systems
Arming condition to be forced by default for Bolt or BQ-deck as parameter
Arming set by external receiver
Emergency stops: crtp generic setpoint , stabilizer stop, Localization system stop
High level commander stop
Supervisor: tumble detection or if usb cable is connected
Kalman_supervisor: resets the Kalman filter if goes out of bounds Kalman filter supervisor reset position
Crazyflie-lib-python Some scripts in theh cflib checks the estimator variance externally
Bootloader powerswitch command controlled from cflib
Commander setpoint timeout (turned off for high level commander)
Watchdog, hard faults and asserts scattered throughout the firmware.
We might find more on the way…

However, if for instance your Crazyflie or Bolt platform loses its positioning in air, or doesn’t have a flowdeck attached before takeoff, there are no default safety systems in check. You either need to catch it, make it land or use an self-made emergency stop button using one of the emergency stop services above.

Safety features in works

As mentioned earlier, we have safety features spread throughout the code base of the Crazyflie firmware. Our current effort is to collect all of these emergency stops and triggers in the supervisor module to have them all in one place.

In addition, since indoor positioning is critical, we want to be notified when it fails. For instance, if the lighthouse geometry is incorrect, we need to see if the position diverges. This check was done outside of the Crazyflie firmware in a cflib script, but it has not been implemented inside the firmware. We also want to provide some options in terms of behavior for these triggers. Currently, we are working on two options: ‘turn the motors off’ or ‘safe land,’ with ‘safe land’ decreasing the thrust while keeping the drone level in attitude.

Furthermore, we want to integrate these features into the cfclient as well. For example, we want to add more emergency safety features to our remote control through the cfclient, and show users how to arm and disarm the vehicle.

These are the elements we are currently working on, but there might be more to come!

Developer meeting May 3rd

You probably already guessed it… the topic about the next developer meeting will be about the safety features in the Crazyflie and the Bolt! We will present the current safety features in the Crazyflie and what we are currently working on to make it better. In this sense, we really want to have your feedback on what you think is important for brushless versions of the Crazyflie for indoor flight!

The Dev meeting will be on Wednesday May the 3rd at 3 PM CEST. Please keep an eye on the discussion forum in the developer meeting thread.

Flapper Drones and positioning systems

2023-04-03 | Matěj Karásek | Leave a comment

This week’s guest blogpost is from Matěj Karásek from Flapper Drones, about flying the Nimble + with a positioning system. Enjoy!

Flapper Drones are bioinspired robots flying by flapping their wings, similar to insects and hummingbirds. If you haven’t heard of Flappers yet, you can read more about their origins at TU Delft and about how they function in an earlier post and on our company website.

In this blogpost, I will write about how to fly the Flappers (namely the Flapper Nimble+) autonomously within a positioning system such as the Lighthouse, and will of course include some nice videos as well.

The Flapper Nimble+ is the first hover-capable flapping-wing drone on the market. It is a development platform powered by the Crazyflie Bolt and so it can enjoy most of the perks of the Crazyflie ecosystem, including the positioning systems as well as other sensors (check this overview). If you would like to get a Flapper yourself, just head to the Bitcraze webstore, where there are some units ready to be shipped! (At the time of writing at least…)

Minimal setup

The minimal setup for flying in a positioning system is nearly identical as with a standard Crazyflie. Next to a Flapper with a recent firmware, a Crazyradio dongle, a positioning system (in this post we will use the Lighthouse), and a compatible positioning deck (Lighthouse deck) you will also need: 1) a mount, such that the deck can be attached on top of the Flapper, and 2) a set of extension cables. You can 3D print the mounts yourself (models here), the extension cable prototypes can either be inquired from Flapper Drones, or can be soldered by yourself (in that case, the battery holder deck, standard Crazyflie pin headers and some wires come handy). Just pay attention to connect the cables in the correct way, as if the deck was mounted right on top of the Bolt. The complete setup with the Lighthouse deck will look like this:

Lighthouse deck installation on a Flapper Nimble+. Make sure the extension cables are well secured (e.g. by using the additional cable mount) such they don’t get caught by the gears.

For the Lighthouse, as with regular Crazyflies, the minimum number of base stations (with some redundancy) is 2, but you will get larger tracking volume with more base stations. 4 base stations mounted at 3 m height will give you about 5 meters time 5 meters coverage, which is recommended especially if you want to fly more than 1 Flapper at a time (they are a bit larger than the Crazyflies, after all…).
From now on, it is exactly the same as with standard Crazyflies. After you calibrate the Lighthouse system using the standard wizard procedure via the Cfclient, you can just go to the Flight Control Tab and use the “Command Based Flight Control” buttons to take-off, command steps in xyz directions and land. It is this easy!

Flapper Nimble+ in Lighthouse flown via Command Based Flight Control of cfclient

Assisted flight demo

We used this setup in February for the demos we were giving at the Highlight Delft festival in the Netherlands. This allowed people with no drone piloting skills (from 3-year-olds, to grandmas – true story) fly and control the Flapper in a safe way (safe for the Flapper, as the Flapper itself is a very safe platform thanks to its soft wings and low weight). To make it more fun, and even safer for the Flapper, we used a gamepad instead of on screen buttons, and we modified the cfclient slightly such that the flight space can be geofenced to stay within the tracking volume.

Flight demo at Highlight Delft festival, using the Lighthouse and position hold assistance

If you would like to try it yourself (it works also with standard crazyflies), the source code is here (just keep in mind it is experimental and has some known bugs…). To fly in the position-assisted mode, you need to press (and keep pressing) the Alt 1 button, and use the joysticks to move around (velocity commands, headless mode). Releasing the Alt 1 button will make the Flapper autoland. Autoland will also get triggered when the battery is low. You can still fly the Flapper in a direct way when pressing Alt 2 instead.

Flying more Flappers at a time

Again, this is something that works pretty much out of the box. As with a regular crazyflie, you just need to assign a unique address to each of the Flappers and then use e.g. this example python script to run a preprogrammed sequence.

With a few extra lines of code, we pulled this quick demo at the end of the Highlight Delft festival, when we had 30 minutes left before packing everything (one of the Flappers decided to drop its landing gear, probably too tired after 3 evenings of almost continuous flying…):

Sequence with 3 Flappers within Lighthouse positioning system

Other positioning systems

Using other positioning systems is equally easy. In fact, for the Loco Positioning system, the deck can even be installed directly on the Flapper’s Bolt board (no extension cables or mounts are needed). As for optical motion tracking, we do not have experience with Qualisys and the active marker deck, but flying with retro-reflective markers within OptiTrack system can be setup easily with just a few hacks.

When choosing and setting up the positioning system, just keep in mind that due to its wings, the Flapper needs to tilt much more to fly forward or sideways, compared to a quadcopter. This is not an issue with the Loco Positioning system (but there can be challenges with position estimation, as described further), but it can be a limitation for systems requiring direct line of sight, such as the Lighthouse or optical motion tracking.

Ongoing work

In terms of control and flight dynamics, the Flapper is very different from the Crazyflie. Thus, for autonomous flight, there remains room for improvement on the firmware side. We managed to include the “flapper” platform into the standard Crazyflie firmware (in master branch since November 2022, and in all releases since then), such that RC flying and other basic functionality works out of the box. However, as many things in the firmware were originally written only for a (specific) quadcopter platform, the Crazyflie 2.x, further contributions are needed to unlock the full potential of the Flapper.

With the introduction of “platforms” last year, many things can be defined per platform (e.g. the PID controller gains, sensor alignment, filter settings, etc.), but e.g. the Extended Kalman filter, and specifically the motion model inside, has been derived and tuned for the Crazyflie 2.x, and is thus no representative of the Flapper with very different flight dynamics. This is what directly affects (and currently limits) the autonomous flight within positioning systems – it works well enough at hover and slow flight, but the agility and speed achievable in RC flight cannot be reached yet. We are planning to improve this in the future (hopefully with the help of the community). The recently introduced out of tree controllers and estimators might be the way to go… To be continued :)

Thanks Matej ! And for those of you at home, don’t forget that we have our dev meeting next Wednesday (the 5th), where we’ll discuss about the Loco positioning system, but also will take some time for general discussions. We hope to see you there!

And we are back!

2022-08-22 | Tobias | Leave a comment

After a period of bitcrazer-vacations, we are now all back at work. The summer here in Sweden has generally been great. Some of us stayed here to keep the company afloat, and some just stayed afloat on lakes or the sea. The majority vacationed inside of Sweden, but some (could you guess who?) have visited France, Italy, or Greece. We’ve been lucky with a mostly warm and sunny weather, perfect for bathing and grilling. And even though it’s nice to enjoy real summer, it’s still worrying sign though, as Europe is experiencing what could be the worst drought in 500 years.

Crazyflie 2.1 back in stock

What is also back is the Crazyflie 2.1, but back in stock, yay! After almost two weeks without any drones available for sale, we received a new batch of our quadcopter today. It should now be available in the shop, just in time for when school starts!

We got some indications the component shortage are slowly moving in the right direction so hopefully it will get easier to keep things in stock in the future. We are keeping our fingers crossed.

Bolt 1.1 ESC cable red/black switched

Unfortunately we recently found out that there has been a manufacturing error with the ESC cables that come with the Bolt 1.1. The black and red cables have been switched. Please see the image below.

With the black and red cables switched this will result in powering your ESCs with reversed polarity. This will most likely burn the MOSFET on the Bolt that controls the power to the ESC, which is the weakest link. This because the MOSFET body diodes on the ESC will conduct and make the whole ESC a short circuit. In many setups, e.g using 4in1 ESC these cables are not used though and will not cause a problem.

Switching the cables back is quite easy to do. Use a needle, tweezer or e.g. small screwdriver to open the plastic lock so the cable can be pulled out. Switch the black and red and you are done. You can double check that the colors are correct by comparing it with the Bolt 1.1 board. The plus and minus should match with the red and black as per the image below:

We are currently working with the manufacturer to get correct cables. If you got a Bolt 1.1 (anytime between June and August 2022) we can of course ship you correct cables once they are ready or give you support if you got problems with the control board. If so, please send us an email to support@bitcraze.io. Sorry for this inconvenience!

Single Actuator Monocopters (SAMs)

2022-08-08 | xinyu | Leave a comment

This week’s guest blogpost is from Xinyu Cai from the research group of ShaoHui Foong, located in the Engineering Product Development Faculty from Singapore University of Technology and Design. Please check out their youtube channel. Enjoy!

Unmanned Aerial Vehicles (UAVs) have garnered much attention from both researchers and engineers in recent decades. Aerial robots in general are classified into mainly three categories: fixed wings, rotary wings and flapping wings.

Fixed wings are one of the most common aerial vehicles as it has relatively higher power efficiency and payload capacity than other types, thanks to their big and highly customizable wing. But this also leads to a bigger footprint and usually the lack of ability for Vertical Taking Off and Landing (VTOL). Rotary wings generally include helicopter and multirotors (such as quadrotors), and they have recently become increasingly popular in our daily lives. Easily achieving great performance in attitude and position control, rotary wings are widely applied in many fields. Flapping wing robots take inspirations from small flapping insects (such as Harvard Robobee) or birds (Purdue Hummingbird Robot).

Fig: A simple prototype of SAM from SUTD with Crazyflie Bolt.

Monocopters are largely inspired from the falling motion of maple seeds, and they are relatively much simpler to build as compared to its counterparts. They can keep a relative smaller footprint and achieve decent control performance although they are highly underactuated. The Single Actuator Monocopter (SAM) has the ability to VTOL, perform 3D trajectory tracking as well as maintain high hovering efficiency. With those advantages, rapid developments have been made in recent years such as the Foldable Single Actuator Monocopter (F-SAM) and Modular Single Actuator Monocopter (M-SAM) from Engineering Product Development (EPD) of Singapore University of Technology and Design (SUTD).

Taking inspiration from nature – Samara inspired monocopter

A descending samara or maple seed, is able to passively enter auto-rotation motion and stabilize its flight attitude, helping to slow down its descent speed and travel further for better survival of the species. This natural behavior attracts interests from scientists and researchers. With previous studies, we learnt that this passive attitude stability is mainly guaranteed by mass distribution (Center of Mass) and wing geometry (Center of Pressure) as well as the rotation motion.

A maple seed inspired Single Actuator Monocopter (SAM).

The SAM is designed to be very close in its mechanical make-up to its natural sibling, having a large single wing structure and a smaller, denser ‘seed’ structure. A single motor with propeller is installed on the leading edge, parallel to the wing surface. Comparing with flight dynamics of the original maple seed, SAM has extra torques and force caused by the spinning propeller, including a reaction torque and thrust directly from propeller, as well as an extra torque caused by precession motion. As a result, the balance of the combined forces and torques allows SAM to enter a new equilibrium condition while still retaining the passive attitude stability.

Development of monocopters

The research on monocopters can be traced back to a long time ago. Here are some examples of different types of air frame to roughly introduce their developments. An air-frame called Robotic Samara [1] was created in 2010, which has a motor to provide rotational force, a servo to control collective pitch of the wing, a winged body fabricated by carbon fiber, and a lipo battery. In the following year, Samarai MAV [2] was developed by following the mass distribution of a natural maple seed. To achieve the control, a servo is equipped to regulate the wing flap. In 2020, a single actuator monocopter was introduced with a simplified air-frame [3]. The main structure is made by laminated balsa wood while the trailing edge of the wing is made by foam for better mass distribution. By making use of the passive attitude stability, only one actuator is required to control the position in 3D space. Based on which, F-SAM [4] and M-SAM [5] were developed in 2021 and 2022 respectively.

SAM with foldable wing structure (F-SAM).

A Modular SAM (M-SAM) with Crazyflie Bolt

Thanks to its easy implementation and reliable performance, we use the Crazyflie Bolt as the flight controller for M-SAM. Like other robotic systems, the ground station is integrated with motion capture system (position and attitude feedback for both control and ground truth) and a joystick (control reference directly generated by user) is responsible for sending filtered state feedbacks and control references or control signal directly to flight controller. This is realized by employing the Crazyradio PA under the Crazyflie-lib-python environment. Simple modifications from the original firmware were made to map from the control reference to motor command (a customized flight controller).

A diagram shows how Crazyflie Bolts work in M-SAM project.

Another advantage of using Crazyflie Bolt in M-SAM project is its open source swarm library. Under the swarm environment, SAMs can fly in both singular and cooperative configurations. With simple human assistance, two SAMs can be assembled into cooperative configuration by making use of a pair of magnetic connectors. The mid-air separation from cooperative configuration to singular configuration is passively triggered by increasing the rotating speed until the centrifugal force overcomes the magnetic force.

Modular Single Actuator Monocopters (M-SAM), which is able to fly in both singular and cooperative configuration.

Potential applications

What kinds of applications can be achieved with the monocopter aerial robotic platform? On the one hand, many applications are limited by the nature of self-rotation motion. On the other hand, the passive rotating body also offers advantages in some special scenarios. For example, SAM is an ideal platform for LIDAR application, which usually requires the rotating motion to sense the environment around. Besides, thanks to simple mechanical design and cheap manufacturing cost, SAM can be designed for one time use such as light weight air deployment or unknown, dangerous environments.

An example [6] shows the potential applications of a rotating robot with camera.

Reference

[1] Ulrich, Evan R., Darryll J. Pines, and J. Sean Humbert. “From falling to flying: the path to powered flight of a robotic samara nano air vehicle.” Bioinspiration & biomimetics 5, no. 4 (2010): 045009.
[2] Fregene, Kingsley, David Sharp, Cortney Bolden, Jennifer King, Craig Stoneking, and Steve Jameson. “Autonomous guidance and control of a biomimetic single-wing MAV.” In AUVSI Unmanned Systems Conference, pp. 1-12. Arlington, VA: Assoc. for Unmanned Vehicle Systems International, 2011.
[3] Win, Luke Soe Thura, Shane Kyi Hla Win, Danial Sufiyan, Gim Song Soh, and Shaohui Foong. “Achieving efficient controlled flight with a single actuator.” In 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), pp. 1625-1631. IEEE, 2020.
[4] Win, Shane Kyi Hla, Luke Soe Thura Win, Danial Sufiyan, and Shaohui Foong. “Design and control of the first foldable single-actuator rotary wing micro aerial vehicle.” Bioinspiration & Biomimetics 16, no. 6 (2021): 066019.
[5] X. Cai, S. K. H. Win, L. S. T. Win, D. Sufiyan and S. Foong, “Cooperative Modular Single Actuator Monocopters Capable of Controlled Passive Separation,” 2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 1989-1995, doi: 10.1109/ICRA46639.2022.9812182.
[6] Bai, Songnan, Qingning He, and Pakpong Chirarattananon. “A bioinspired revolving-wing drone with passive attitude stability and efficient hovering flight.” Science Robotics 7, no. 66 (2022): eabg5913.

H-ModQuad: Modularity for Versatility

2022-07-25 | David | Leave a comment

This week we have a guest blog post from Jiawei Xu and David Saldaña from the Swarmslab at Lehigh University. Enjoy!

Limits of flying vehicles

Advancements in technology have made quadrotor drones more accessible and easy to integrate into a wide variety of applications. Compared to traditional fixed-wing aircraft, quadrotors are more flexible to design and more suitable for motioning, such as statically hovering. Some examples of quadrotor applications include photographers using mounting cameras to take bird’s eye view images, and delivery companies using them to deliver packages. However, while being more versatile than other aerial platforms, quadrotors are still limited in their capability due to many factors.

First, quadrotors are limited by their lift capacity, i.e., strength. For example, a Crazyflie 2.1 is able to fly and carry a light payload such as an AI deck, but it is unable to carry a GoPro camera. A lifter quadrotor that is equipped with more powerful components can transport heavier payload but also consumes more energy and requires additional free space to operate. The difference in the strength of individual quadrotors creates a dilemma in choosing which drone components are better suited for a task.

Second, a traditional quadrotor’s motion in translation is coupled with its roll and pitch. Let’s take a closer look at Crazyflie 2.1, which utilizes a traditional quadrotor design. Its four motors are oriented in the same direction – along the positive z-axis of the drone frame, which makes it impossible to move horizontally without tilting. While such control policies that convert the desired motion direction into tilting angles are well studied, proven to work, and implemented on a variety of platforms [1][2], if, for instance, we want to stack a glass filled with milk on top of a quadrotor and send it from the kitchen to the bedroom, we should still expect milk stains on the floor. This lack of independent control for rotation and translation is another primary reason why multi-rotor drones lack versatility.

*Fig 1. A crazyflie has four propellers generating thrust forces in parallel. Credit to:* *https://robots.ros.org/crazyflie/*

Improving strength

These versatility problems are caused by the hardware of a multi-rotor drone designed specifically to deal with a certain set of tasks. If we push the boundary of these preset tasks, the requirements on the strength and controllability of the multi-rotor drone will eventually be impossible to satisfy. However, there is one inspiration we take from nature to improve the versatility in the strength of multi-rotor drones – modularity! Ants are weak individual insects that are not versatile enough to deal with complex tasks. However, when a group of ants needs to cross natural boundaries, they will swarm together to build capable structures like bridges and boats. In our previous work, ModQuad [3], we created modules that can fly by themselves and lift light payloads. As more ModQuad modules assemble together into larger structures, they can provide an increasing amount of lift force. The system shows that we can combine weak modules with improving the versatility of the structure’s carrying weight. To carry a small payload like a pin-hole camera, a single module is able to accomplish the task. If we want to lift a heavier object, we only need to assemble multiple modules together up to the required lift.

Improving controllability

On a traditional quadrotor, each propeller is oriented vertically. This means the device is unable to generate force in the horizontal direction. By attaching modules side by side in a ModQuad structure, we are aligning more rotors in parallel, which still does not contribute to the horizontal force the structure can generate. That is how we came up with the idea of H-ModQuad — we would like to have a versatile multi-rotor drone that is able to move in an arbitrary direction at an arbitrary attitude. By tilting the rotors of quadrotor modules and docking different types of modules together, we obtain a structure whose rotors are not pointing in the same direction, some of which are able to generate a force along the horizontal direction.

H-ModQuad Design

H-ModQuad has two major characteristics: modularity and heterogeneity, which can be indicated by the “Mod” and “H-” in the name. Modularity means that the vehicle (we call a structure) is composed of multiple smaller modules which are able to fly by themselves. Heterogeneity means that we can have modules of different types in a structure.

As mentioned before, insects like ants utilize modularity to enhance the group’s versatility. Aside from a large number of individuals in a swarm that can adapt to the different scales of the task requirement, the individuals in a colony specializing in different tasks are of different types, such as the queen, the female workers, and the males. The differentiation of the types in a hive helps the group adapt to tasks of different physical properties. We take this inspiration to develop two types of modules.

In our related papers [4][5], we introduced two types of modules which are R-modules and T-modules.

*Fig 2. Major components of an H-ModQuad “T-module” we are using in our project. We use Bitcraze Crazyflie Bolt as the central control board.*

An example T-module is shown in the figure above. As shown in the image, the rotors in a T-module are tilted around its arm connected with the central board. Each pair of diagonal rotors are tilted in the opposite direction, and each pair of adjacent rotors are either tilting in the same direction or in the opposite direction. We arrange the tilting of the rotors so that all the propellers generate the same thrust force, making the structure torque-balanced. The advantage of the T-module is that it allows the generation of more torque around the vertical axis. One single module can also generate forces in all horizontal directions.

An R-module has all its propellers oriented in the same direction that is not on the z-axis of the module. In this configuration, when assembling multiple modules together, rotors from different modules will point in different directions in the overall structure. The picture below shows a fully-actuated structure composed of R-modules. The advantage of R-modules is that the rotor thrusts inside a module are all in the same direction, which is more efficient when hovering.

*Structure 1: Composed of four types of R-modules.*

Depending on what types of modules we choose and how we arrange those modules, the assembled structure can obtain different actuation capabilities. Structure 1 is composed of four R-modules, which is able to translate in horizontal directions efficiently without tilting. The picture in the intro shows a structure composed of four T-modules of two types. It can hover while maintaining a tilting angle of up to 40 degrees.

Control and implementation

We implemented our new geometric controller for H-ModQuad structures based on Crazyflie Firmware on Crazyflie Bolt control boards. Specifically, aside from tuning the PID parameters, we have to change the power_distribution.c and controller_mellinger.c so that the code conforms to the structure model. In addition, we create a new module that embeds the desired states along predefined trajectories in the firmware. When we send a timestamp to a selected trajectory, the module retrieves and then sends the full desired state to the Mellinger Controller to process. All modifications we make on the firmware so that the drone works the way we want can be found at our github repository. We also recommend using the modified crazyflie_ros to establish communication between the base station and the drone.

Videos

Challenges and Conclusion

Different from the original Crazyflie 2.x, Bolt allows the usage of brushless motors, which are much more powerful. We had to design a frame using carbon fiber rods and 3-D printed connecting parts so that the chassis is sturdy enough to hold the control board, the ESC, and the motors. It takes some time to find the sweet spot of the combination of the motor model, propeller size, batteries, and so on. Communicating with four modules at the same time is also causing some problems for us. The now-archived ROS library, crazyflie_ros, sometimes loses random packages when working with multiple Crazyflie drones, leading to the stuttering behavior of the structure in flight. That is one of the reasons why we decided to migrate our code base to the new Crazyswarm library instead. The success of our design, implementation, and experiments with the H-ModQuads is proof of work that we are indeed able to use modularity to improve the versatility of multi-rotor flying vehicles. For the next step, we are planning to integrate tool modules into the H-ModQuads to show how we can further increase the versatility of the drones such that they can deal with real-world tasks.

Reference

[1] D. Mellinger and V. Kumar, “Minimum snap trajectory generation and control for quadrotors,” in 2011 IEEE International Conference on Robotics and Automation, 2011, pp. 2520–2525.

[2] T. Lee, M. Leok, and N. H. McClamroch, “Geometric tracking control of a quadrotor uav on se(3),” in 49th IEEE Conference on Decision and Control (CDC), 2010, pp. 5420–5425.

[3] D. Saldaña, B. Gabrich, G. Li, M. Yim and V. Kumar, “ModQuad: The Flying Modular Structure that Self-Assembles in Midair,” 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, pp. 691-698, doi: 10.1109/ICRA.2018.8461014.

[4] J. Xu, D. S. D’Antonio, and D. Saldaña, “Modular multi-rotors: From quadrotors to fully-actuated aerial vehicles,” arXiv preprint arXiv:2202.00788, 2022.

[5] J. Xu, D. S. D’Antonio and D. Saldaña, “H-ModQuad: Modular Multi-Rotors with 4, 5, and 6 Controllable DOF,” 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 190-196, doi: 10.1109/ICRA48506.2021.9561016.

Flapper Drones – bioinspired robots powered by Crazyflie Bolt

2022-07-11 | Matěj Karásek | Leave a comment

As the Crazyflie ecosystem expands, more and more novel aerial (but also ground or hybrid) robots are being built with one of the Crazyflie controllers onboard. For recent examples, you can check e.g. the recent blogpost about ICRA 2022.

In this post, I will introduce yet another Crazyflie-Bolt-powered aerial robot, the Flapper Nimble+ from our company Flapper Drones, which unlike other flying robots doesn’t have any propellers but uses flapping wings instead.

The best aerial robot design is…

Small drones, or micro air vehicles, have seen a lot of progress and new developments in the last 20 years. The most widespread design nowadays is a quadcopter, such as the Crazyflie 2.1. But is a quadcopter the ultimate (micro) drone solution? At Flapper Drones, we believe nature might provide even better designs… For some applications at least! 😊

Flying like a bird…

Flapper Drones is a spinoff of the MAVLab of the Delft University of Technology. At the MAVLab, we have been researching bio-inspired flight as part of the DelFly project since 2005. From the beginning, the goal has been to develop a lightweight, mission capable micro air vehicle, the design of which would draw inspiration from nature. Over the years, many such MAV concepts have been designed, built and tested, including the DelFly Micro, the world’s smallest camera-equipped MAV, or the DelFly Explorer, the first autonomous flapping-wing MAV equipped with a stereovision system. All these designs were propelled by a pair of flapping wings, while being controlled (and passively stabilized) by a tail such as birds or men-made airplanes.

… or an insect

The latest design, the DelFly Nimble is insect-inspired instead. What does that mean? The Nimble has no tail, which would provide the damping needed for stable flight. Instead, it is stabilized actively, by adjustments of the motion of its flapping wings. This is what all flying insects and also hummingbirds do. Flies, for example, sense their body motions with their halteres, drum-stick like biological gyroscopes, and adapt their wing motion accordingly to stay balanced…. or to be agile, when someone is trying to swat them!

And while the Nimble was originally built just to demonstrate that an insect-inspired flying robot can be built, eventually we could also use it to learn more about the flight of insects:

Flapper Drones – how do they work?

The Flapper Nimble+ is the commercial (and enlarged) version of the DelFly Nimble, developed and produced by Flapper Drones. To our knowledge, it is the first, and so far the only hover-capable tailless flapping-wing drone available!

The thrust keeping the Nimble+ airborne is created by its four flapping wings, which flap back and forth horizontally, about 10 to 12 times per second.

The wing actuation mechanism allows to adjust the flapping frequency of the left and right wing pairs independently, which enables control of the roll rotation. Pitch rotation is controlled by adjusting the mean wing position within the stroke plane, which shifts the mean thrust force forward or backward with respect to the center of mass, and also introduces a stabilizing dihedral angle in forward flight. Finally, yawing motion is achieved by tilting the wing roots of the left and right wing pair asymmetrically:

Advantages of flapping wings

The use of flapping-wing drones such as the Flapper Nimble+ brings several advantages. Next to their attractive biological appearance, the soft flapping wings produce less intrusive, low frequency sound and are safer, compared to propellers. As the wings move back and forth, minor mid-air collisions are not a problem. The wings bounce off objects leaving no damage, and the drone keeps flying as this only represents a minor disturbance:

The aerial drag characteristic is also different and helps with precise indoor flight. As soon as zero attitude is commanded, the Nimble+ goes into halt in a matter of several wingbeats, making it an ideal choice for novice drone pilots as well as in constrained or cluttered indoor spaces. Finally, the flapping wings can provide additional lift force as they also glide in forward flight. This can improve the power efficiency by over 20%, compared to hovering.

Otherwise, Flapper Drones can be operated as any other drone, with vertical take offs and landings, quick maneuvers and flight in any direction:

Crazyflie Bolt & compatibility

The Flapper Nimble+ is powered by the Crazyflie Bolt 1.1, where the Bolt’s BMI088 IMU and STM32F4 MCU are suitable substitutes to the halteres and brains of the real fly. We made this choice, because this enables compatibility with most of the Crazyflie ecosystem, but also, because we felt the only way a Crazyflie would do justice to its name is if it had flapping wings😊

Currently, the Nimble+ uses a fork of the Crazyflie firmware, which is of course open source. Moreover, with the recently introduced platform functionality, we will be able to include the Flapper platform into the official crazyflie firmware very soon (expected still in July 2022). This means that the Flapper remains compatible with the official Python libraries, the PC client or the smartphone app. But also third-party projects like the Crazyswarm or the Skybrush should only require minor adjustments, if any, to operate a swarm of Flappers. Thus, for the existing Crazyflie users, switching from a Crazyflie to the Flapper should be a breeze!

The Flapper Nimble+ is hardware compatible with most of the Crazyflie expansion decks. While software support remains experimental (the Flapper Nimble+ is not a native Crazyflie product, after all), many of the decks work out of the box and others might need just minor firmware modifications. Would you like to fly the Nimble+ autonomously? Add an LPS or Lighthouse deck and you’re good to go!

For more details regarding deck compatibility, you can check this overview.

Applications

While the Nimble+ was originally designed for drone shows and similar entertainment applications, the open-source firmware and expansion decks enabling autonomous flight make it ideal also as for academic research and, in general, as a development platform. Are you researching swarming, and would you like to make your swarm even more bio-inspired? Are you developing new sensors, or new controllers (possibly even bioinspired), which you would like to test on a new type of flying platform? Are you interested in the aerodynamics of flapping wings, or the flight dynamics of insect-like flight? Or are you just curious and would you like to learn more about bioinspired flight? In all these cases, a Flapper might be what you are looking for!

The 114-g and 49-cm wide Flapper Nimble+ has been designed as a modular system where any part can easily be replaced. Flapper Drones provides all the spares, which are available upon request. If you are interested in using the Nimble+ for entertainment, rather than research, you can modify the appearance by creating your own body shells, which can also be illuminated by RGB Leds (a suitable interface and power supply is already integrated). Or even by altering the design of the wings. Finally, you can easily extend the Flapper with your own sensors, or other devices. Would you like to add a tail? A gripper? A perching device? This is all possible, as long as these additions fit within the payload limit of about 25 grams.

Available soon in the webstore!

Did you get (bio)inspired, and would you like to try an insect-like flying robot yourself? Then we have some good news! The Flapper Nimble+ will soon be available for sale in an exclusive partnership with Bitcraze and their webstore. Checkout the product description and leave your email address behind, such that you get a notification when the Flappers are in stock and ready to ship. The first batch of 10 units is expected to be available at the end of summer, so do not wait too long 😉

Want to learn more?

To learn more about Flapper Drones, you can check our website, or watch the talk I gave at the last miniBAM:

ICRA 2022: Crazyflie in Robotic Research

2022-06-13 | Kimberly McGuire | Leave a comment

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.

⚡ ‘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
- IEEE Xplore Page
- Video
🐝 ‘A Fast and Efficient Attitude Control Algorithm of a Tilt-Rotor Aerial Platform Using Inputs Redundancies’ Su et al. from UCLA
- IEEEXplore page
- Video
⚡x2 ‘Cooperative Modular Single Actuator Monocopters Capable of Controlled Passive Separation’, Cai et al. from Singapore University of Technology & Design
- IEEEXplore page
- ICRA 2022 Outstanding Dynamics and Control Paper Winner!
🐝’Optimal Inverted Landing in a Small Aerial Robot with Varied Approach Velocities and Landing Gear Designs’ Habas et al. from Penn State
🐝 ‘PogoDrone: Design, Model, and Control of a Jumping Quadrotor’, Zhu et al from Lehigh U.
🐝 ‘Clustering and Informative Path Planning for 3D Gas Distribution Mapping: Algorithms and Performance Evaluation’, Ercolani et al from EPFL
- IEEEXplore page
🐝 ‘A Bimodal Rolling-Flying Robot for Micro Level Inspection of Flat and Inclined Surfaces’ , Pimentel et al from Instituto Superior Tecnico
- IEEEXplore page
🐝x 2 ‘Collision Avoidance for Multiple Quadrotors Using Elastic Safety Clearance Based Model Predictive Control’, Jin et al. from USTC & Sina
- IEEEXplore page
🐝 + ⚡🦋 ‘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
- ArXiv
- IEEEXplore page
🐝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.
- IEEEXplore page

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:

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.
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.

The BAMs are back!

2022-04-04 | Barbara | Leave a comment

You surely remember that last fall, to celebrate our 10 year anniversary, we organized a 3 days online conference on our own. We actually loved it, and you seemed to like it to. So we’ve been contemplating the possibility of having another, on a smaller format.

And after some thoughts, we are glad to announce the Mini BAMs! As the name implies, they are shorter (maximum 3 hours if the discussions get lively), with a simplified platform (to be determined yet), but still with interesting talks, and a lot to discover from speakers and the community. Each Mini BAM will be dedicated to a specific subject, with one or two guest speakers, followed by discussions.

We already have a session programmed, so let’s see what we have in store for our very first Mini BAM!

When? The 18th of May, in the afternoon (CEST)(the exact time will be determined shortly)

What ? Our focus this time is shows in the sky! You surely couldn’t have missed that drones are getting more and more involved in shows and productions. But while aerial entertainment is getting popular, its implementation is not easy. At Bitcraze, we try to accompany artists to help them create a unique experience, but it’s not our main area of expertise. that’s why we’re turning to 2 close partners for those shows in the sky. Which lead me to….

Who ? We will have two distinguished speakers with us this afternoon.

Gábor Vásárhelyi was born in Budapest, Hungary, in 1979. He received his MSc in engineering-physics from the Technical University of Budapest, Hungary, in 2003, and his PhD in technical sciences (info-bionics) from Péter Pázmány Catholic University, Hungary, in 2007. Since 2009 he is with Eötvös University, Department of Biological Physics as leader of the Robotic Lab at Tamas Vicsek’s Research Group on collective motion. Since 2015, he is the CEO of CollMot Robotics Ltd., a spinoff dedicated to multi-drone services. His research fields are connected to the collective motion and collective behavior of animals and robots (drones). He received many awards, for exemple: Junior Prima Award, category of informatics (2007), Magyary Postdoctoral Grant (2013), Bolyai János Research Scholarship (2015), ELTE Innovative Researcher Award (2021).

You may recognize Gabor as the author of this post. For this Mini BAM, he will present us with Skybrush, his very clean platform for any kind of swarm/fleet/multi-UAV mission control.

We will also be joined by Matěj Karásek.

Matěj Karásek studied mechanical engineering and holds a PhD in engineering sciences. He spent 10 years in the academia (ULB Brussels, TU Delft) researching animal flight and developing bioinspired flying robots. He is a founder of Flapper Drones, a startup company developing bird-like robots for research and entertainment applications.

Matej will talk to us about his Bolt-based drone, that is set up with flapping wings!

You will have time to ask them questions, and be sure to stay afterwards for discussions about show drones, the Bolt, and Skybrush!

If you’re interested in joining, follow this link to pre-register:

https://forms.gle/spDpKqhrus7WrHYJ8

More informations will of course come soon, stay updated!

Batteries in the shop

And now, for something completely different: you may have noticed that it’s difficult to order batteries with us these past weeks. That’s due to a change in transport regulation for Lithium batteries. Thankfully, we got a certification last week that allows us to ship batteries without the limitations that we had to put in the shop. We’re working on getting everything up to par with the new regulations, and shipping only batteries should soon be possible. Finally, the Swarm bundles will be, for a short time, sold without any chargers as we’re out of stock for those. The prices have been regulated accordingly.

What’s in store for 2022?

2022-01-03 | Barbara | Leave a comment

We’ve had an exciting year in 2021, and we’re eager to see what 2022 will bring ! Let’s see what’s in the pipeline and what we hope for this new year.

Products

The AI deck and Bolt out of Early Access

We’ve put a lot of efforts during these last months on working with the AI deck’s firmware and infrastructure. With great help of our intern Rik, we managed to make huge leaps, and hopefully sometimes in the coming months we’ll be able to share what we worked on. I can already tell you that the incoming release will bring some needed improvements on flashing on the GAP8 chip and improved image streaming! As the AI deck is one of the most challenging of our decks, we also hope to add an extensive tutorial (that we call the “mega tutorial”) to help you working with it.

Also we have started to push some framework changes to make it easier for you to make bigger drones with the Crazyflie Bolt. One of those are the persistent parameter system that we have recently implemented on the Crazyflie’s, so we will add more and more of these types of features. The hope is, is that we are able to provide some kind of assembly kit for a larger Bolt-based drone, of which we already did some initial battery investigations for.

Prototypes

Fun Fridays are usually our time to play around with new possibilities and prototypes. Marcus has already made great strides, and hopefully in 2022 we’ll be able to go even farther with those. Arnaud has also been working on the much waited new iteration of the Crazyradio, with a new chip and an improved communication protocol. Tobias, our dedicated hardware man, has also ideas down the pipes in the form of a brushless Crazyflie as we already showed in our future plans presentation of November’s BAMdays. Also we hope to initiate the design process of a new and improved version of the Crazyflie with more power and processing capabilities.

People and Collaborations

Last year we have continued 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. It proves really fruitful, both for us and the people we talk to, so we hope 2022 will see yet again closer and newer connections.

We were really happy with our first own online conference, which helped us reconnect and talk to our community about all the awesomeness achieved with the Crazyflies. We hope to implement something similar on a more regular basis, to keep talking about collaborations, possibilities, and in general sharing all the work that’s been done on the platform. Those “lightweight” BAM should arrive soon, so keep updated if you want to join them!

Component shortage and productions issues

We expect to still deal with the component shortage, as it is expected to last for at least another year, even two. Production is therefore a continuous challenge, with a lot of unpredictability, and we will find better solutions to deal with it in 2022. Thankfully, we have good hopes on keeping good stock levels throughout the crisis, as we’ve increased our stock. We’ll of course keep you updated on any big updates regarding the crisis and how it is affecting it us.

Unfortunately, the component shortage also means that it’s harder to make prototypes. It’s difficult to find and/or buy just one chip, so it causes delays in our creative hardware developments. It is what it is… but we will sure be able to find solutions – as we did during our 10 years’ history!

Anything else?

Of course our heads are always full of ideas and we are passionate to work on anything! We have ambitions in developing a simulation for our users or CI, doing more measurements with the new thrust stand or adding further improvements to our documentation and tutorials. And we might also meet new interesting people (digitally or in person?) who might give us enough inspiration to start something completely new! Soon we will have our quarterly meeting, where we try to herd and select our passions and ideas into conceivable plans and actions.

With all these exciting projects, we’re really excited to see what 2022 has in store for us! I hope you too have an awesome year 2022.

Powerful Persistent Parameters

2021-12-06 | Jonas Danielsson | 4 Comments

The Crazyflie parameter framework provides a way to get, set and monitor parameters in the quadcopter. Examples of a parameter include which effect the LED ring will display as well as which controller to use for flight.

The parameters have default values and up until now have been reset to those default values on each restart of the Crazyflie. This has not been seen as much of a problem (Or has it? Let us know!) since most use of the Crazyflie platform has been session based and the need for persistent parameters has been low. Our work with getting the Crazyflie Bolt out of early access has however changed this need.

The Bolt will need different values for the tuning parameters for controllers and being forced to set these on each boot would be pretty annoying. And since we want the Crazyflie Bolt and the Crazyflie 2.1 to share the same firmware, persistent parameters would come in handy.

Fortunately the Crazyflie includes an EEPROM (Electronically Erasable Programmable Read-Only Memory) which we can use to store parameter values and have them survive restarts of the quad.

So this means, with the latest branches of the firmware and the python library, you can set values of a persistent parameter, store it to EEPROM, and the parameter will keep its values across reset and even across firmware upgrades.

Persistent Parameter API

Not all parameters will be able to be persistent and stored in the EEPROM. We have added a way to declare a parameter as persistent in the firmware:

PARAM_ADD_CORE(PARAM_UINT8 | PARAM_PERSISTENT, effect, &effect)

This will allow the new API added to our python library to be used with this parameter. The API consists of three actions:

Getting the state of a persistent parameter
Storing the current value of a persistent parameter
Clearing the stored value of a persistent parameter

The state of a persistent parameter consist of three pieces of information:

Is the value stored or not
The default value of the parameter
The stored value of the parameter

Setting a value, using the regular parameter API, is not enough to store the value to the EEPROM for a persistent parameter, you need to be explicit. A special API call is needed to store the current value to memory. And to stop storing the value you need to use the clear API action.

Python API

The above choices corresponds to three methods in our Python API:

def persistent_get_state(self, complete_name, callback)
Code language: PHP (php)

Get the state of the specified persistent parameter. The state will be returned in the supplied callback. The state is represented as a named tuple with members: is_stored, default_value and stored_value. The state is None if the parameter is not persistent or if something goes wrong.

def persistent_store(self, complete_name, callback=None)Code language: PHP (php)

Store the current value of the specified persistent parameter to EEPROM. The supplied callback will be called with True as an argument on success, and with False as an argument on failure.

def persistent_clear(self, complete_name, callback=None)
Code language: PHP (php)

Clear the current value of the specified persistent parameter from EEPROM. The supplied callback will be called with True as an argument on success and with False as an argument on failure.

Example code

We have also added an example script that will showcase the functionality, it will list the state of all persisted parameters in the firmware, and will store and clear some of them. The output when run against current master is:

$ CFLIB_URI=radio://0/80/2M/E7E7E7E7E8 python3 examples/parameters/persistent_params.py 
-- All persistent parameters --
sound.effect: PersistentParamState(is_stored=False, default_value=0, stored_value=None)
ring.effect: PersistentParamState(is_stored=True, default_value=6, stored_value=2)

Set parameter ring.effect to 10

Store the new value in persistent memory
Persisted ring.effect!
The new state is:
ring.effect: PersistentParamState(is_stored=True, default_value=6, stored_value=10)

Clear the persisted parameter
Cleared ring.effect!
The new state is:
ring.effect: PersistentParamState(is_stored=False, default_value=6, stored_value=None)Code language: PHP (php)

You can count on more parameters to be marked as persistent in the near future. Hopefully this will be useful for you! Please report any issues you find!

Happy Hacking!