Your quad-copter is hovering nicely 100 feet north of you, its camera pointed exactly on target. The hover is doing so well all the RC transmitter controls are in the neutral position. The wind picks up a bit and now the ‘copter is 110 feet north. You adjust its position with your control stick but as you do the wind dies and you overshoot the correction. Another gust pushed it away from target in more than one direction as frustration passes your lips: ARGGGHH!! You promise yourself to get a new flight computer with position hold capability.
How do multicopters with smart controllers hold their position? They use a technique called Proportional – Integral – Derivative (PID) control. It’s a concept found in control systems of just about everything imaginable. To use PID your copter needs sensors that measure the current position and movement.
The typical sensors used for position control are a GPS receiver and an Inertial
Management Measurement Unit (IMU) made up of an accelerometer, a gyroscope, and possibly a magnetometer (compass). Altitude control would require a barometer or some other means of measuring height above ground. Using sensor fusion techniques to combine the raw data, a computer can determine the position, movement, and altitude of the multicopter. But calculating corrections that will be just right, without over or undershooting the goal, is where PID comes into play. Continue reading “Flying with Proportional – Integral – Derivative Control”
[Aerotenna] recently announced the first successful flight of an unmanned air vehicle (UAV) powered by a Xilinx Zynq processor running ArduPilot. The Zynq is a dual ARM processor with an onboard FPGA that can offload the processor or provide custom I/O devices. They plan to release their code to their OcPoC (Octagonal Pilot on a Chip) project, an open source initiative that partners with Dronecode, an open source UAV platform.
Continue reading “Flying High with Zynq”
Imagine you’re a farmer trying to grow a crop under drought conditions. Up-to-the-minute data on soil moisture can help you to decide where and when to irrigate, which directly affects your crop yield and your bottom line. More sensors would mean more data and a better spatial picture of conditions, but the cost of wired soil sensors would be crippling. Wireless sensors that tap into GSM or some sort of mesh network would be better, but each sensor would still need power, and maintenance costs would quickly mount. But what if you could deploy a vast number of cheap RFID-linked sensors in your fields? And what if an autonomous vehicle could be tasked with the job of polling the sensors and reporting the data? That’s one scenario imagined in a recent scholarly paper about a mobile Internet of Things (PDF link).
In the paper, authors [Jennifer Wang], [Erik Schluntz], [Brian Otis], and [Travis Deyle] put a commercially available quadcopter and RC car to the hack. Both platforms were fitted with telemetry radios, GPS, and an off-the-shelf RFID tag reader and antenna. For their sensor array, they selected passive UHF RFID tags coupled to a number of different sensors, including a resistance sensor used to measure soil moisture. A ground-control system was developed that allowed both the quad and the car to maneuver to waypoints under GPS guidance to poll sensors and report back.
Beyond agriculture, the possibilities for an IoT based on cheap sensors and autonomous vehicles to poll them are limitless. The authors rightly point out the challenges of building out a commercial system based on these principles, but by starting with COTS components and striving to keep installed costs to a minimum, we think they’ve done a great proof of concept here.
Your mission, should you choose to accept it, is to send a quadcopter to near space and return it safely to the Earth. Getting it there is not that difficult. In fact, you can get pretty much anything you want to near space with a high altitude weather balloon. Getting it back on the ground in one piece is a whole other ballgame.
Why does someone need to do this? Well, it appears the ESA’s StarTiger team is taking a card out of NASA’s book and wants to use a Sky Crane to soft land a rover on Mars. But instead of using rockets to hold the crane steady in the Martian sky, they want to use…you guessed it, a quadcopter. They’re calling it the Dropter.
At first glance, there seems to be a lot wrong with this approach. The atmosphere on Mars is about 100 times less dense than the Earth’s atmosphere at sea level. How do props operate in these conditions? Testing would need to be done of course, and the Earth’s upper atmosphere is the perfect place to carry out such testing. At 100,000 feet, the density of the stratosphere is about the same as that of the Martian surface atmosphere. AND 100,000 feet is prime high altitude balloon territory. Not to mention the gravity on Mars is about 38% of Earth’s gravity, meaning a 5.5 pound model on Earth could accurately represent a 15 pound model on Mars.
With all of these facts taken into consideration, one can conclude that realistic testing of a scale model Martian quadcopter is within the grasp of the hacker community. We’ve seen some work on high altitude drones before, but never a quadcopter.
Now it’s your turn to do something no one has ever done before. Think you got what it takes to pull such a project off? Let us know what your approach to the challenge would be in the comments.
Continue reading “Ask Hackaday: Quadcopter in Near Space?”
Is it a quadcopter? A plane? No, it’s both! [Daniel Lubrich] is at it again with a vertical take off and landing transformer he calls the SkyProwler.
The SkyProwler uses a switch blade type mechanism to move from quadcopter mode to plane mode. The wings can be detached to make it a normal quad that has all the typical bells and whistles. It can follow you around with GPS, fly autonomously via way points, and has this cool gimbal mechanism that keeps the GoPro stable as the drone pitches in flight, allowing for a better video experience.
[Dan’s] ultimate goal is a full size passenger model called the SkyCruiser, which uses the same switchblade transformation mechanism as his much smaller SkyProwler. Be sure to check out the video below if you haven’t already, and let us know of any quadcopter / plane hybrids of your own.
Correction: We previously associated [Daniel Lubrich] with the ATMOS program. This was in error and has been removed from the article. The ATMOS UAV is a separate project which we previously covered.
Continue reading “Quadcopter Plane Transformer is Awesome”
One of the acronyms you may hear thrown around is DDS which stands for Direct Digital Synthesis. DDS can be as simple as taking a digital value — a collection of ones and zeroes — and processing it through a Digital to Analog Converter (DAC) circuit. For example, if the digital source is the output of a counter that counts up to a maximum value and resets then the output of the DAC would be a ramp (analog signal) that increases in voltage until it resets back to its starting voltage.
This concept can be very useful for creating signals for use in a project or as a poor-man’s version of a signal or function generator. With this in mind I set out here to demonstrate some basic waveforms using programmable logic for flexibility, and a small collection of resistors to act as a cheap DAC. In the end I will also demonstrate an off-the-shelf and inexpensive DDS chip that can be used with any of the popular micro-controller boards available that support SPI serial communication.
All of the topics covered in the video are also discussed further after the break.
Continue reading “Direct Digital Synthesis (DDS) Explained by [Bil Herd]”
[Horiken Engineering], which is made up of engineering students at the department of aerospace at the University of Tokyo have developed an autonomous quadcopter that requires no external control — and its tiny. By using two cameras and a sonar sensor, the quadcopter is capable of flying by itself due to its ability to process the data from the on-board sensors. To do the complex data processing fast enough to fly, it is using a Cortex-M4 MCU, a Spartan-6 FPGA, and 64MBs of DDRSDRAM. It also has the normal parts of a quadcopter, plus gyros, a 3D printed frame and a 3-axis compass. The following video demonstrates the quadcopter’s tracking ability above a static image (or a way point). The data you see in real-time is only the flight log, as the quadcopter receives no signal — it can only transmit data.
Continue reading “Autonomous Quadcopter Fits in the Palm of your Hand”