Taming Robot Arm Jump with Accelerometers

Last fall, I grabbed a robot arm from Robot Geeks when they were on sale at Thanksgiving. The arm uses servos to rotate the base and move the joints and gripper. These work well enough but I found one aspect of the arm frustrating. When you apply power, the software commands the servos to move to home position. The movement is sufficiently violent it can cause the entire arm to jump.

This jump occurs because there is no position feedback to the Arduino controller leaving it unable to know the positions of the arm’s servos and move them slowly to home. I pondered how to add this feedback using sensors, imposing the limitation that they couldn’t be large or require replacing existing parts. I decided to try adding accelerometers on each arm section.

Accelerometers, being affected by gravity when on a planet, provide an absolute reference because they always report the direction of down. With an accelerometer I can calculate the angle of an arm section with respect to the direction of gravitational acceleration.

Before discussing the accelerometers, take a look at the picture of the arm. An accelerometer would be added to each section of the arm between the controlling servos.

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Flying with Proportional – Integral – Derivative Control

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”

Converting Kids’ Hand-Drawings to G-Code

[Martin Raynsford] wrote a program that converts a black-and-white 2D image to G-code so that his laser printer could then etch the image. Not satisfied with just that, he used his laser printer to make a scanner that consists of a stand for his webcam and a tray below it for positioning the paper just right. The result was something he took to a recent Maker Faire where many kids drew pictures on paper which his system then scanned and laser etched.

Screenshot of Martin's scanning and G-code maker program
Martin’s scanning and G-code maker program

[Martin’s] program, written in C#, does the work of taking the image from the webcam using OpenGL and scanning it line by line looking for pixels that surpass a contrast threshold. For each suitable pixel the program then produces G-code that moves the laser to the corresponding coordinate and burns a hole. Looking at the source code (downloadable from his webpage) it’s clear from commented-out code that he did plenty of experimenting, including varying the laser burn time based on the pixel’s brightness.

While it’s a lot of fun writing this code as [Martin] did, after the break we talk about some off-the-shelf ways of accomplishing the same thing.

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Code Craft: Cross Compiling for the Raspberry Pi

Sometimes there’s just no place like your desktop. You’ve already got your favorite development tools and references setup or installed and it’s a pain when you’re trying to work on an unfamiliar, or simply uncustomized, system. On your desktop everything is at your fingertips. If you want to search the web, the browser is just an alt-tab away. If you need a calculator, it’s right there to run. Your editor highlights syntax in your favorite colors already.

When developing on a Raspberry Pi, you leave all these creature comforts behind unless you spend the time to configure the Pi to your liking. Then it all gets wiped when you install a new distribution, like the recent change from Wheezy to Jessie. Even then it’s frustrating to switch back and forth between the desktop and the Pi because there is always something on the other system that you need. My usual comment is, “dirty word”, literally.

Cross-developing on your desktop is a very workable solution. We’re going to walk through setting up your desktop and a Pi to do this. This means loading a Pi ARM toolchain on your desktop and a debugging server on the Pi. This’ll let you develop and debug from in the comfort of your desktop. An added advantage is when you put that Pi in a robot you can debug over a wireless link.

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Code Craft-Embedding C++: Hacking the Arduino Software Environment

The Arduino software environment, including the IDE, libraries, and general approach, are geared toward education. It’s meant as a way to introduce embedded development to newbies. This is a great concept but it falls short when more serious development or more advanced education is required. I keep wrestling with how to address this. One way is by using Eclipse with the Arduino Plug-in. That provides a professional development environment, at least.

The code base for the Arduino is another frustration. Bluntly, the use of setup() and loop() with main() being hidden really bugs me. The mixture of C and C++ in libraries and examples is another irritation. There is enough C++ being used that it makes sense it should be the standard. Plus a good portion of the library code could be a lot better. At this point fixing this would be a monumental task requiring many dedicated developers to do the rewrite. But there are a some things that can be done so let’s see a couple possibilities and how they would be used.

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Code Craft – Embedding C++: Templates

The language C++ is big. There is no doubting that. One reason C++ is big is to allow flexibility in the technique used to solve a problem. If you have a really small system you can stick to procedural code encapsulated by classes. A project with a number of similar but slightly different entities might be best addressed through inheritance and polymorphism.

A third technique is using generics, which are implemented in C++ using templates. Templates have some similarities with #define macros but they are a great deal safer. The compiler does not see the code inserted by a macro until after it has been inserted into the source. If the code is bad the error messages can be very confusing since all the developer sees is the macro name. A template is checked for basic syntax errors by the compiler when it is first seen, and again later when the code is instantiated. That first step eliminates a lot of confusion since error messages appear at the location of the problem.

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ATtiny Does 170×240 VGA With 8 Colors

The Arduino is a popular microcontroller platform for getting stuff done quickly: it’s widely available, there’s a wealth of online resources, and it’s a ready-to-use prototyping platform. On the opposite end of the spectrum, if you want to enjoy programming every bit of the microcontroller’s flash ROM, you can start with an arbitrarily tight resource constraint and see how far you can push it. [lucas][Radical Brad]’s demo that can output VGA and stereo audio on an eight-pin DIP microcontroller is a little bit more amazing than just blinking an LED.

[lucas][RB] is using an ATtiny85, the larger of the ATtiny series of microcontrollers. After connecting the required clock signal to the microcontroller to get the 25.175 Mhz signal required by VGA, he was left with only four pins to handle the four-colors and stereo audio. This is accomplished essentially by sending audio out at a time when the VGA monitor wouldn’t be expecting a signal (and [lucas][Rad Brad] does a great job explaining this process on his project page). He programmed the video core in assembly which helps to optimize the program, and only used passive components aside from the clock and the microcontroller.

Be sure to check out the video after the break to see how a processor with only 512 bytes of RAM can output an image that would require over 40 KB. It’s a true testament to how far you can push these processors if you’re determined. We’ve also seen these chips do over-the-air NTSC, bluetooth, and even Ethernet.

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