Designing An Advanced Autonomous Robot: Goose

Robotics is hard, maybe not quite as difficult as astrophysics or understanding human relationships, but designing a competition winning bot from scratch was never going to be easy. Ok, so [Paul Bupe, Jr’s] robot, named ‘Goose’, did not quite win the competition, but we’re very interested to learn what golden eggs it might lay in the aftermath.

The mechanics of the bot is based on a fairly standard dual tracked drive system that makes controlling a turn much easier than if it used wheels. Why make life more difficult than it is already? But what we’re really interested in is the design of the control system and the rationale behind those design choices.

The diagram on the left might look complicated, but essentially the system is based on two ‘brains’, the Teensy microcontroller (MCU) and a Raspberry Pi, though most of the grind is performed by the MCU. Running at 96 MHz, the MCU is fast enough to process data from the encoders and IMU in real time, thus enabling the bot to respond quickly and smoothly to sensors. More complicated and ‘heavier’ tasks such as LIDAR and computer vision (CV) are performed on the Pi, which runs ‘Robot operating system’ (ROS), communicating with the MCU by means of a couple of ‘nodes’.

The competition itself dictated that the bot should travel in large circles within the walls of a large box, whilst avoiding particular objects. Obviously, GPS or any other form of dead reckoning was not going to keep the machine on track so it relied heavily on ‘LiDAR point cloud data’ to effectively pinpoint the location of the robot at all times. Now we really get to the crux of the design, where all the available sensors are combined and fed into a ‘particle filter algorithm’:

What we particularly love about this project is how clearly everything is explained, without too many fancy terms or acronyms. [Paul Bupe, Jr] has obviously taken the time to reduce the overall complexity to more manageable concepts that encourage us to explore further. Maybe [Paul] himself might have the time to produce individual tutorials for each system of the robot?

We could well be reading far too much into the name of the robot, ‘Goose’ being Captain Marvel’s bazaar ‘trans-species’ cat that ends up laying a whole load of eggs. But could this robot help reach a de-facto standard for small robots?

We’ve seen other competition robots on Hackaday, and hope to see a whole lot more!

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A Tiny Train Departure Board, Just Like The Real Thing

If you travel on the British rail system, you’ll be familiar with the ubiquitous orange dot-matrix departure display boards. At a glance they tell you the expected arrival times of the next few trains, where they are headed, and at the bottom the current time.  [Chris Crocker-White] was inspired by a Tweet to recreate one of these displays in miniature and hang it under his monitor.

The hardware is a Raspberry Pi Zero with an OLED screen, in a custom 3D-printed case. A soldered USB cable takes power from the monitor’s USB ports. Software wise it’s a demonstration vehicle for the Balena cloud service that pulls its data from their transport API, but the choice of dot matrix typeface is perfect and absolutely looks the part.

There is some question as to whether a project such as this one should need a cloud service as its backend, and of course it serves as a demonstration piece rather than a definitive way to enact a departure board. It does however bring a ready-packaged API for transport data, which given that many data sources can be opaque, is a useful feature.

Train time displays seem to be a popular choice on the Eastern side of the Atlantic, here’s another British one, and one from Ireland.

Thanks [Pyrofer] for the tip.

BootBasic Fits Your Favorite Language In The Boot Sector

Humans seem to have a need to do things that aren’t practical. Make the biggest ball of twine. Engrave the Declaration of Independence on a grain of rice. We want to make things bigger, smaller, faster, or whatever. That might explain why [nanochess] put out bootBASIC.

The 8088 (or later) assembly code gives you a very restricted BASIC interpreter that you can boot up. That means it has to fit in the 512-byte boot block that the hardware loads to get an operating system running. How restricted? Keep in mind it fits in 512 bytes. Each line can only have 19 characters or less. Backspace works, but doesn’t update the screen. Line numbers range from 1 to 999 and there are only 26 integer variables named a through z that hold 16 bits. All statements are in lower case.

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Neural Network In Glass Requires No Power, Recognizes Numbers

We’ve all come to terms with a neural network doing jobs such as handwriting recognition. The basics have been in place for years and the recent increase in computing power and parallel processing has made it a very practical technology. However, at the core level it is still a digital computer moving bits around just like any other program. That isn’t the case with a new neural network fielded by researchers from the University of Wisconsin, MIT, and Columbia. This panel of special glass requires no electrical power, and is able to recognize gray-scale handwritten numbers.

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ESP32 Gets Advance Windowed Apps Using This VGA GUI Library

We featured [Fabrizio Di Vittorio]’s FabGL library for the ESP32 back in April of this year. This library allows VGA output using a simple resistor based DAC (3 resistors for 8 colors; 6 resistors for 64 colors), and includes functions for PS/2 mouse and keyboard input, a graphics library, and many of the miscellaneous functions you might need to develop games on the ESP32. Now, a GUI interface library has been added to ease application development.

The GUI, of course, runs on the VGA output. The library includes what you’d expect from a minimal windowing GUI, like keyboard and mouse support, windows with the usual minimize/maximize/close controls, and modal and message dialog boxes. For input controls, there are labels, text boxes, buttons, radio buttons, checkboxes, normal and editable combo boxes, and listboxes — you know, pretty much everything you need to develop a modern GUI application. All the code is open-source (GPL 3.0) and in the GitHub repo.

While the original FabGL had a game-development orientation, the addition of this new GUI functionality opens up a new range of applications. If you want to find out more about using the FabGL library, you can check out our previous coverage of the mostly game-oriented functions.

You can get a look at the new GUI functions in action in the video, after the break.

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Making An Update Server For PythonAnywhere And GitHub

Cloud based IDEs and development tools have grown over the years, though most have limitations in their free tiers and may not be fully compatible with other services such as GitHub. [Aadi Bajpai] loved using PythonAnywhere and to collaborate using GitHub, so he made a update server that automatically updates the running code once you make a push to Github

PythonAnywhere gives you access to a python shell over a web browser, and also lets you run a web app that can be accessed via a custom sub-domain. Even though it does not have direct integration with GitHub, you can drop to the bash shell to and get access to a git client.

For this hack, [Aadi Bajpai] utilizes the webhooks from GitHub that are triggered when a push event is detected. A flask server running on PythonAnywhere is written such that once triggered by the get POST request, it locally executes a git pull from the repository. There a bit more work that allows adding a bit of security sauce to the recipe but it is a pretty elegant solution and can be used for other cases as well.

Setting up alert notifications has been demonstrated to be an interesting task, though integrating Discord or Slack for notifications adds a little more bragging rights.

Caching In On Program Performance

Most of us have a pretty simple model of how a computer works. The CPU fetches instructions and data from memory, executes them, and writes data back to memory. That model is a good enough abstraction for most of what we do, but it hasn’t really been true for a long time on anything but the simplest computers. A modern computer’s memory subsystem is much more complex and often is the key to unlocking real performance. [Pdziepak] has a great post about how to take practical advantage of modern caching to improve high-performance code.

If you go back to 1956, [Tom Kilburn’s] Atlas computer introduced virtual memory based on the work of a doctoral thesis by [Fritz-Rudolf Güntsch]. The idea is that a small amount of high-speed memory holds pieces of a larger memory device like a memory drum, tape, or disk. If a program accesses a piece of memory that is not in the high-speed memory, the system reads from the mass storage device, after possibly making room by writing some part of working memory back out to the mass storage device.

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