The inspiration for this article is Mike the Headless Chicken. The story of Mike is one of the more bizarre episodes in history, an accident that became a rural American legend. In 1945, a farmer in Fruita, Colorado, attempted to butcher a chicken for dinner but missed the jugular vein and left part of the brain stem intact. Amazingly, the bird survived and continued to walk, perch, and even attempt to peck for over 18 months.
The pursuit of Artificial General Intelligence (AGI) has ignited a geopolitical competition of historic proportions. This is a massive technological arms race, with leaders like Vladimir Putin saying whoever achieves AGI first will “rule the world”. There are parallels with the nuclear arms race, which tends to get peoples attention, but is this comparison accurate? And what does it all mean for a country like Australia, a tech savvy, middle power, caught in the middle of this tussle?
For the purposes of this article, we will define AGI as at or above human level intelligence, and acknowledge that this vague description doesn’t capture the wider issues, about what intelligence is and how we measure it.
If you are using AI at the moment, then it is probably based on a model of the human neocortex. All of the current Large Language Models (LLMs) are overwhelmingly inspired by this approach. These architectures are great at abstract reasoning, pattern recognition, and language generation which are all tasks that are analogous to higher-order cortical functions. But is this the path to AGI? We don’t think it is, for reasons that will be explored in this article.
Interested in what planes are flying over your location? Want to know how high they are and how fast they are going? Want to build your own ADS-B (Automatic Dependent Surveillance-Broadcast) ground station that can be installed anywhere and receive real-time data directly from airplanes on your computer? In 2017 we wrote a couple of articles about tracking planes using ADS-B, and it is time for an update!
The 2017 version used a 4D Systems 2.4″ touchscreen HAT for a display, USB DVB-T TV Tuner RTL2832U + R820T as our Software Defined Radio (SDR), and ran PiAware on a Raspberry Pi 3 Model B (v1.2). The 2023 version uses all new and upgraded hardware. Read all about it, on our latest Medium article.
There will come a point where you will want to store data which isn’t lost when your microprocessor loses power. This is particularly handy for storing calibration or configuration values, to save you having to re-calibrate some piece of hardware (e.g., IMUs, and servos) every time the power cycles. One solution for Arduino boards is using EEPROM (Electrically Erasable Programmable Read-Only Memory).
EEPROM is a type of non-volatile ROM that enables individual bytes of data to be erased and reprogrammed. It is used to store small amounts of data which are written occasionally and then read multiple times.
EEPROM is often contained within the microprocessor, and different boards will have different amounts. For example, the ATMega328P used in the UNO R3 and Nano, has 1024 bytes (1KB) of EEPROM. It is organized as a separate data space, and the EEPROM data bytes are addressed linearly between 0 and 1023.
Our example application will save calibration data for six servo motors. This is well suited to saving in EEPROM as it doesn’t often change and reading the values are not time critical. You can read the full Arduino EEPROM article on Medium.
The Stewart Platform, also known as a hexapod, motion base or parallel manipulator, is a mechanical system that consists of a platform connected to a fixed base through six independently actuated legs. This arrangement allows for precise and versatile motion control in all six degrees of freedom (DOF): three translational (surge, sway, heave) and three rotational (roll, pitch, yaw).
In the context of flight simulators, the Stewart Platform is utilized to replicate the dynamic movements and sensations experienced by pilots during flight. It provides a realistic simulation of aircraft motion, enabling pilots and trainees to practice flying maneuvers, emergency procedures, and various flight scenarios in a controlled environment. By synchronizing the movement of the platform with visual and auditory cues, flight simulators enhance the training experience and help pilots develop their skills without the risks associated with actual flight.
The Stewart platform is used in car/flight/VR simulators, machine tool technology, animatronics, crane technology, underwater research, simulation of earthquakes, air-to-sea rescue, mechanical bulls, satellite dish positioning, the Hexapod-Telescope, robotics, and orthopedic surgery.
We will be using it to test our drone flight control hardware, IMUs and associated software. You can read the full Stewart Platform article on Medium.
The Reefwing AHRS library provides an Attitude and Heading Reference System (AHRS) class for use with Arduino compatible boards. The library has been tested with the Arduino Nano, Nano 33 BLE, Nano 33 BLE SENSE (REV 1 and REV 2), Nano 33 IoT, MKR Vidor 4000, Portenta H7 and the Seeed XIAO nRF52840 Sense boards.
An Attitude and Heading Reference System (AHRS) takes information from the Inertial Measurement Unit (IMU) and processes it to provide reliable roll, pitch and yaw angles.
We needed an instrument that can plot the voltage/thrust curve for any BLDC motor and propeller combination. We use Pulse Width Modulation to control the Electronic Speed Controller which drives the motor, and it would be nice to be able to relate the PWM percentage to thrust. Our first prototype used Force Sensing Resistors which will be compared to load cells. #arduino #fsr #dyno #shield
https://reefwing.medium.com/an-arduino-dc-motor-dynamometer-shield-part-1-54efd0c3e7e6
IMUs with 3 sensors each measuring 3-axes, pump out a lot of data. It can be difficult to work out how your IMU is performing, which is why the free open source data visualisation tool from x-io Technologies is so great. It is available for all major operating systems (Windows, macOS, and Linux). #arduino #imu #datavisualisation #datavisualization
Read all about it in our latest article on Medium:
In Part 1 we introduced our Arduino based ESC and followed this in Part 2 with an explanation of the power stage and MOSFET drivers. Part 3 focusses on the bootstrap capacitor which is part of the driver circuit used to turn the high-side MOSFET hard on. #arduino #bldcmotor #esc #bootstrapcapacitor #IR2110
https://reefwing.medium.com/an-arduino-nano-electronic-speed-controller-esc-part-3-e17392bd2887