Variable-Nozzle Ducted Fan Provides Fluid Dynamics Lessons

Any student new to the principles of fluid dynamics will be familiar with Bernoulli’s principle and the Venturi effect, where the speed of a liquid or gas increases when the size of the conduit it flows through decreases. When applying this principle to real-world applications, though, it can get a bit more complex than a student may learn about at first, mostly due to the shortcomings of tangible objects when compared to their textbook ideals. [Mech Ninja] discovered this while developing a ducted fan based around an RC motor.

The ducted fan is meant to be a stand-in for a model jet engine, based around a high-powered motor generally designed for drone racing. Most of the build is 3D printed including duct system, but in order to improve the efficiency and thrust beyond simple ducting, [Mech Ninja] designed and built a variable nozzle to more finely control the “exhaust” of his engine. This system is also 3D printed and can restrict or open up the outflow of the ducted fan, much like a real jet engine would. It uses two servos connected to collars on the outside of the engine. When the servos move the collars, a set of flaps linked to the collars can choke or expand the opening at the rear of the engine.

This is where some of the complexity of real-life designs comes into play, though. After testing the system with a load cell under a few different scenarios, the efficiency and thrust weren’t always better than the original design without the variable nozzle. [Mech Ninja] suspects that this is due to the gaps between the flaps, allowing air to escape and disrupting the efficient laminar flow of the air leaving the fan, and plans to build an improved version in the future. Fluid dynamics can be a fairly complex arena to design within, sometimes going in surprising directions like this ducted fan that turned out better than the theory would have predicted, at least until they accounted for all the variables in the design.

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Stretching The Flight Time On A Compressed Air Plane

[Tom Stanton] has been experimenting with compressed air motors on model aircraft for a good few years, but keeping them aloft (and intact) for more than a few seconds has proven a tough nut to crack. His latest design represents a breakthrough — pulling off an impressive 1 minute and 26 seconds flight on 4 liters of compressed air.

The model incorporates an enhanced engine design featuring an expanding seal on the piston, a concept inspired by the old Air Hogs toy plane. For the airframe, he constructed lightweight wings using 3D printed ABS ribs on a carbon spar and reinforcing rods, all of which were wrapped in heat shrink film. Additionally, [Tom] incorporated a thin balsa former along the leading edge of the wing to help maintain its shape. The fuselage is also composed of a carbon fiber tube, and is outfitted with printed fittings to install the wings, V-tail, RC electronics, and soda/air bottles. A hollow nylon bolt holds the two bottles together end-to-end while allowing the motor to be screwed directly onto the front bottle. To conserve weight, each of the two V-tail control surfaces are actuated by single cables linked to servos, with piano wire torsion springs in the hinges to maintain tension

Despite successful flights, [Tom]’s trials were not without challenges. One crash threatened severe damage to his airframe, but thanks to a central 3D printed bracket that absorbed most of the impact, total destruction was avoided. Similarly, a printed shaft saved his expensive carbon fiber propeller from being damaged during multiple landings, an outcome that led [Tom] to devise a readily replaceable consumable connector.

A second video after the break offers a behind-the-scenes insights into this project including some fascinating technical details. For more on this project’s history, take a look at the initial diaphragm engines and his attempts to make them fly.

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3D Printed Mini Drone Test Gimbal

Drones are a pain, especially mini ones. When you are designing, building (or even reviewing) them, they inevitably fly off in some random direction, inevitably towards your long-suffering dog, hit him in the butt and send him scuttling off in search of a quieter spot for a nap.

[Tristan Dijkstra] and [Suryansh Sharma] have a solution: a mini-drone test gimbal. The two are in the the Networked Systems group and the Biomorphic Intelligence Lab who use CrazyFlie drones in their work, which require regular calibration and testing. This excellent design allows the drone to rotate in three dimensions, while still remaining safely contained. That means I could test the flight characteristics of a drone without endangering my dogs important napping schedule.

Efforts involved attaching a light tether that restricts the drone until we know how the it flies, but what usually happens is that the tether gets trapped in a rotor, or the tether gets tight and the drone freaks out and crashes into the ground.

Using a gimbal is far more elegant, because it allows the drone to rotate freely in three dimensions, so the basic features of the drone can be established before you let it loose in the skies.

The gimbal was designed with the CrazyFlie in mind, but as there’s nothing more exotic holding the craft down than a zip tie, it should work with similarly sized quadcopters.

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Control Tricks For Tailsitters

An RC VTOL aircraft always makes for a compelling project, but ensuring the transition between hover and forward flight can be quite challenging. In the video after the break, [Nicholas Rehm] demystifies of the flight control algorithm required for a VTOL tailsitter.

Tailsitters are one of the simplest VTOL arrangements, the testbed here being a simple foam KF airfoil wing with two motors and two servo-controlled elevons. As with almost all his projects [Nicholas], uses of his open-source dRehmFlight flight controller to demonstrate the practical implementation of the control algorithm.

Three major factors that need to be simultaneously taken into account when transitioning a tailsitter VTOL. First off, yaw becomes roll, and vice versa. This implies that in hover mode, elevons have to move in opposite directions to control yaw; however, this same action will make it roll in forward flight. The same applies for differential thrust from motors — it controls roll in hover and yaw in forward flight. Nevertheless, this change of control scheme only works if the flight controller also alters its reference frame for “level” flight (i.e., flips forward 90°). As [Nicholas] demonstrates, failing to do so results in a quick and chaotic encounter with the ground.

With these adjustments made, the aircraft can transition to forward flight but will oscillate pitch-wise as it overcorrects while trying to maintain stable flight; this is due to PID gains – 3rd factor. The deflection required by control surfaces is much more aggressive during hover mode; thus PID gains need to be reduced during forward flight. A final improvement involves adding a brief delay when switching modes for smoother rotation.

For more interesting VTOL configurations, check out [Tom Stanton]’s RC V-22 Osprey, and this solar recharging trimotor

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Autonomous Racing Drones Are Starting To Beat Human Pilots

Even with all the technological advancements in recent years, autonomous systems have never been able to keep up with top-level human racing drone pilots. However, it looks like that gap has been closed with Swift – an autonomous system developed by the University of Zurich’s Robotics and Perception Group.

Previous research projects have come close, but they relied on optical motion capture settings in a tightly controlled environment. In contrast, Swift is completely independent of remote inputs and utilizes only an onboard computer, IMU, and camera for real-time for navigation and control. It does however require a pretrained machine learning model for the specific track, which maps the drone’s estimated position/velocity/orientation directly to control inputs. The details of how the system works is well explained in the video after the break.

The paper linked above contains a few more interesting details. Swift was able to win 60% of the time, and it’s lap times were significantly more consistent than those of the human pilots. While human pilots were often faster on certain sections of the course, Swift was faster overall. It picked more efficient trajectories over multiple gates, where the human pilots seemed to plan one gate in advance at most. On the other hand human pilots could recover quickly from a minor crash, where Swift did not include crash recovery.

The final results are impressive, especially given that all the processing and sensing comes from the drone. However, it still requires a well mapped track, so a human pilot should still come out on top given limited information about a new track. It would also be interesting to see how it handles large courses with gates that are much further apart.

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Tiny Drone Racing Gate Records Your Best Laps

Professional drone racing is now an elite sport, with all the high-end tech, coverage, and equipment that goes along with it. If you’re just practicing with tiny drones in your home though, you might not be so well equipped. You might want to build something like this tiny FPV drone racing gate from [ProfessorBoots] to help keep track of laptimes while you’re training.

The build uses ultrasonic range sensors to detect when an object passes through the gate. The gate itself consists of a ring of addressable LEDs in strip form. The gate switches from green to red as a visual indicator of a drone passing through the gate. There’s also a small 2.4-inch touch screen that displays laptimes and enables the gate to be configured quickly and easily. The gate also serves up a webpage on the local network for viewing laptimes in a browser.

It does bear noting that at this stage, it’s primarily a practice tool. The gate doesn’t currently work for proper competitions, as it has no way of determining which drone might be flying through the gate at any one time.

It’s not the first time we’ve seen a TinyWhoop drone, either. Video after the break.

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Automated Drone Takes Care Of Weeds

Commercial industrial agriculture is responsible for providing food to the world’s population at an incredibly low cost, especially when compared to most of human history when most or a majority of people would have been involved in agriculture. Now it’s a tiny fraction of humans that need to grow food, while the rest can spend their time in cities and towns largely divorced from needing to produce their own food to survive. But industrial agriculture isn’t without its downsides. Providing inexpensive food to the masses often involves farming practices that are damaging to the environment, whether that’s spreading huge amounts of synthetic, non-renewable fertilizers or blanket spraying crops with pesticides and herbicides. [NathanBuildsDIY] is tackling the latter problem, using an automated drone system to systemically target weeds to reduce his herbicide use.

The specific issue that [NathanBuildsDIY] is faced with is an invasive blackberry that is taking over one of his fields. To take care of this issue, he set up a drone with a camera and image recognition software which can autonomously fly over the field thanks to Ardupilot and a LiDAR system, differentiate the blackberry weeds from other non-harmful plants, and give them a spray of herbicide. Since drones can’t fly indefinitely, he’s also build an automated landing pad complete with a battery swap and recharge station, which allows the drone to fly essentially until it is turned off and uses a minimum of herbicide in the process.

The entire setup, including drone and landing pad, was purchased for less than $2000 and largely open-source, which makes it accessible for even small-scale farmers. A depressing trend in farming is that the tools to make the work profitable are often only attainable for the largest, most corporate of farms. But a system like this is much more feasible for those working on a smaller scale and the automation easily frees up time that the farmer can use for other work. There are other ways of automating farm work besides using drones, though. Take a look at this open-source robotics platform that drives its way around the farm instead of flying.

Thanks to [PuceBaboon] for the tip!

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