Almost two years ago, a research team showed that it was possible to get fine motor control from cheap, brushless DC motors. Normally this is not feasible because the motors are built-in such a way that the torque applied is not uniform for every position of the motor, a phenomenon known as “cogging”. This is fine for something that doesn’t need low-speed control like a fan motor, but for robotics it’s a little more important. Since that team published their results, though, we are starting to see others implement their own low-speed brushless motor controllers.
The new method of implementing anti-cogging maps out the holding torque required for any position of the motor’s shaft so this information can be used later on. Of course this requires a fair amount of calibration; [madcowswe] reports that this method requires around 5-10 minutes of calibration. [madcowswe] also did analysis of his motors to show how much harmonic content is contained in these waveforms, which helps to understand how this phenomenon arises and how to help eliminate it.
While [madcowswe] plans to add more features to this motor control algorithm such as reverse-mapping, scaling based on speed, and better memory usage, it’s a good implementation that has visible improvements over the stock motors. The original research is also worth investigating if a cheaper, better motor is something you need.
Here on Hackaday, too often do we turn our heads and gaze at the novelty of 3D printing functional devices. It’s easy to forget that other techniques for assembling functional prototypes exist. Here, [Reuben] nails the aspect of functional prototyping with the laser cutter with a real-world application: a roll-pitch friction differential drive built from just off-the shelf and laser-cut parts!
The centerpiece is held together with friction, where both the order of assembly and the slight wedged edge made from the laser cutter kerf keeps the components from falling apart. Pulleys transfer motion from the would-be motor mounts, where the belts are actually tensioned with a roller bearing mechanism that’s pushed into position. Finally, the friction drive itself is made from roller-blade wheels, where the torque transferred to the plate is driven by just how tightly the top screw is tightened onto the wheels. We’d say that [Reuben] is pushing boundaries with this build–but that’s not true. Rather, he’s using a series of repeatable motifs together to assemble a both beautiful and complex working mechanism.
This design is an old-school wonder from 2012 uncovered from a former Stanford course. The legendary CS235 aimed to teach “unmechanically-minded” roboticists how to build a host of mechanisms in the same spirit as MIT’s How-to-make-almost-Anything class. While CS235 doesn’t exist anymore, don’t fret. [Reuben] kindly posted his best lectures online for the world to enjoy.
Robot design traditionally separates the body geometry from the mechanics of the gait, but they both have a profound effect upon one another. What if you could play with both at once, and crank out useful prototypes cheaply using just about any old 3D printer? That’s where Interactive Robogami comes in. It’s a tool from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) that aims to let people design, simulate, and then build simple robots with a “3D print, then fold” approach. The idea behind the system is partly to take advantage of the rapid prototyping afforded by 3D printers, but mainly it’s to change how the design work is done.
To make a robot, the body geometry and limb design are all done and simulated in the Robogami tool, where different combinations can have a wild effect on locomotion. Once a design is chosen, the end result is a 3D printable flat pack which is then assembled into the final form with a power supply, Arduino, and servo motors.
A white paper is available online and a demonstration video is embedded below. It’s debatable whether these devices on their own qualify as “robots” since they have no sensors, but as a tool to quickly prototype robot body geometries and gaits it’s an excitingly clever idea.
Sudoku is a great way to pass some time, especially on a long flight. However, we don’t think the airlines will let [Sanahm] board with his sudoku-solving robot. The basic machine looks like a 2D plotter made with aluminum extrusion, with the addition of a Raspberry Pi and a camera. The machine can read a sudoku puzzle, solve it, and then fill in the puzzle with a pen. Unlike humans, it should never need to erase its work.
The software uses OpenCV to process the camera data, find the grid, and the cells provided by the puzzle. TensorFlow recognizes the numbers. From there, it is all just math to solve the puzzle. Once solved, the plotter part of the robot takes over and fills in the blanks. After all that, this seems like the easy part.
[Jeremy Cook]’s latest take on the Strandbeest, the ClearWalker, is ready to roll! He’s been at work on this project for a while, and walks us through the electronics and control system as well as final assembly tweaks. The ClearWalker is fully controllable and includes a pan and tilt camera as well as programmable LED segments, and even a tail.
When we last saw [Jeremy] at work on this design, it wasn’t yet functional. He showed us all the important design and assembly details that went into creating a motorized polycarbonate version of [Theo Jansen’s] classic Strandbeest design; there’s far more to the process than simply scaling parts up or down. Happily, [Jeremy] is able to show off the crystal clear beauty in his photo gallery as well as a new video, embedded below.
Stepper motors are a great solution for accurate motion control. You’ll see them on many 3D printer designs since they can precisely move each axis. Steppers find uses in many robotics projects since they provide high torque at low speeds.
Since steppers are used commonly used for multi-axis control systems, it’s nice to be able to wire multiple motors back to a single controller. We’ve seen a few stepper control modules in the past that take care of the control details and accept commands over SPI, I2C, and UART. The AnanasStepper 2.0 is a new stepper controller that uses CAN bus for communication, and an entry into the 2017 Hackaday Prize.
A CAN bus has some benefits in this application. Multiple motors can be connected to one controller via a single bus. At low bit rates, it can work on kilometer long busses. The wiring is simple and cheap: two wires twisted together with no shielding requirements. It’s also designed to be reliable in high noise environments such as cars and trucks.
The project aims to implement an API that will allow control from many types of controllers including Arduino, Linux CNC, several 3D printer controllers, and desktop operating systems. With a few AnanasSteppers one of these controllers, you’d be all set up for moving things on multiple axes.
His latest project is quite exciting. He has incorporated his robotic glockenspiel with a hacked hard drive rhythm section to play audio controlled via a PIC 16F84A microcontroller. The song choice is Axel-F. If you had a cell phone around the early 2000’s you were almost guaranteed to have used this song as a ringtone at some point or another. This is where music is headed these days anyway; the sooner we can replace the likes of Justin Bieber with a robot the better. Or maybe we already have?