Summary of Arduino customisable artificial intelligence and gesture recognition
This article describes an untethered gesture recognition controller developed by the Arduino Team using an Arduino Nano 33 BLE Sense. The device utilizes its onboard 9-axis motion sensor to detect hand-drawn numbers when a button is pressed, wirelessly sending commands to peripherals like a robotic arm. This project demonstrates how compact AI can enable embedded intelligence for edge control and maker projects with minimal resources.
Parts used in the Untethered Gesture Recognition Controller:
- Arduino Nano 33 BLE Sense
- 9-axis motion sensor
- Button
- Robotic arm
If you are interested in artificial intelligence and gesture recognition you may be interested in a new article published to the official Arduino blog this week by the Arduino Team. Using a Arduino Nano 33 BLE Sense and untethered gesture recognition controller has been created using the boards 9-axis motion sensor. When a button is pressed, the user draws a number in the air, and corresponding commands are wirelessly sent to peripherals. In this case, a robotic arm. Check out the video below to learn more about gesture recognition and artificial intelligence.
One AI will do any task we ask of it. But in reality, even when AI reaches the advanced levels we envision, it won’t automatically be able to do everything. The Fraunhofer Institute for Microelectronic Circuits and Systems has been giving this a lot of thought. As a test case, an Arduino Nano 33 BLE Sense was employed to build a demonstration device. Using only the onboard 9-axis motion sensor, the team built an untethered gesture recognition controller. When a button is pressed, the user draws a number in the air, and corresponding commands are wirelessly sent to peripherals. In this case, a robotic arm.”
“Obviously this is just an example use case. It’s easy to see the massive potential that this kind of compact, learning AI could have. Whether it’s in edge control, industrial applications, wearables or maker projects. If you can train a device to do the job you want, it can offer amazing embedded intelligence with very few resources.”
For more information on the Arduino customizable artificial intelligence and gesture recognition testing and prognosis jump over to the official Arduino blog by following the link below.
Source: Arduino customisable artificial intelligence and gesture recognition
- What hardware was used to build the demonstration device?
An Arduino Nano 33 BLE Sense was employed as the test case. - How does the user send commands to the peripherals?
The user presses a button and draws a number in the air to send corresponding commands wirelessly. - Which specific sensor enables the gesture recognition?
The device uses only the onboard 9-axis motion sensor. - Can this technology be applied to industrial settings?
Yes, the article notes massive potential for industrial applications among other fields. - Does the AI require extensive resources to function?
No, it offers amazing embedded intelligence with very few resources. - What peripheral was used in this specific example?
A robotic arm served as the peripheral receiving the wireless commands. - Where can I find more information on this project?
More details are available on the official Arduino blog. - Is this system tethered or wireless?
The project creates an untethered gesture recognition controller.
