Real Time Object Detection For $59

There was a time when making a machine to identify objects in a camera was difficult, even without trying to do it in real time. But now, you can do it with a Jetson Nano board for under $60. How well does it work? Watch [Murtaza’s] video below and see what you think.

The first few minutes of the video piqued our interest, and good thing, too, because the 50 lines of code get a 50-plus minute video! It is worth watching, though, because there’s a lot of good information about how to apply this technique in your own projects.

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Open Source Self-Driving Smartphone Robot

Our smartphones are incredibly powerful computers in their own right, yet we don’t often see them directly integrated into projects. Intel Intelligent Systems Lab has done exactly that with the release OpenBot, an open source smartphone based self-driving robot.

Most of the magic happens on the smartphone, which runs an app built on TensorFlow Lite, and integrates the camera and array of sensors on the smartphone, as well as the data from ultrasonic sensors and wheel encoders on the robot. The robot itself is relatively simple, with four geared DC motors, motor drivers wired to an Arduino Nano that interfaces with an Android Phone over serial.

The app created by the Intel ISL team comes preloaded with three AI models that can do either person following, or two different modes of autonomous navigation. By connecting a Bluetooth controller to the smartphone and drive the robot around manually in your specific environment while collecting data, you can train a custom autonomous driving policy to suit your environment.

This looks like an excellent way to get a taste of autonomous robots on a small budget, while still being a viable base for more demanding applications. We’ve seen only a few smartphone based robots like DriveMyPhone and SmartiPresense, which don’t have AI capabilities, but are intended for telepresence applications. We’ve always wondered why we don’t see more projects with cellphones, so we welcome the example.

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OPARP Telepresence Robot

[Erik Knutsson] is stuck inside with a bunch of robot parts, and we know what lies down that path. His Open Personal Assistant Robotic Platform aims to help out around the house with things like filling pet food bowls, but for now, he is taking one step at a time and working out the bugs before adding new features. Wise.

The build started with a narrow base, an underpowered RasPi, and a quiet speaker, but those were upgraded in turn. Right now, it is a personal assistant on wheels. Alexa was the first contender, but Mycroft is in the spotlight because it has more versatility. At first, the mobility was a humble web server with a D-pad, but now it leverages a distance sensor and vision, and can even follow you with a voice command.

The screen up top gives it a personable look, but it is slated to become a display for everything you’d want to see on your robot assistant, like weather, recipes, or a video chat that can walk around with you. [Erik] would like to make something that assists the elderly who might need help with chores and help connect people who are stuck inside like him.

Expressive robots have long since captured our attention and we’re nuts for privacy-centric personal assistants.

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Pixy2 Is Super Vision For Arduino Or Raspberry Pi

A Raspberry Pi with a camera is nothing new. But the Pixy2 camera can interface with a variety of microcontrollers and has enough smarts to detect objects, follow lines, or even read barcodes without help from the host computer. [DroneBot Workshop] has a review of the device and he’s very enthused about the camera. You can see the video below.

When you watch the video, you might wonder how much this camera will cost. Turns out it is about $60 which isn’t cheap but for the capabilities it offers it isn’t that much, either. The camera can detect lines, intersections, and barcodes plus any objects you want to train it to recognize. The camera also sports its own light source and dual servo motor drive meant for a pan and tilt mounting arrangement.

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DIY Switches For People Who Can’t Push Switches

An outstanding number of things most people take for granted present enormous hurdles for people with physical disabilities, including interaction with computers and other digital resources. Assistive technologies such as adaptive switches allow users who cannot use conventional buttons or other input devices to interact with digital devices, and while there are commercial offerings there is still plenty of room for projects like [Cassio Batista]’s DIY Low-cost Assistive Technology Switches.

[Cassio]’s project focuses on non-contact switches, such as proximity and puff-based activations. These are economical, DIY options aimed at improving accessibility for people who are unable to physically push even specialized switches. There are existing products in this space, but cost can be a barrier and DIY options that use familiar interfaces greatly improves accessibility.

Assistive technologies that give people the tools they need to have more control over their own lives in a positive, healthy way is one of the more vibrant and positive areas of open hardware development, and it’s not always clear where the challenges lie when creating solutions. An example of this is the winner of the 2015 Hackaday Prize, the Eyedrivomatic, which allows one to interface the steering of an electric wheelchair to a gaze tracking system while permanently altering neither device; a necessity because users often do not own their hardware.

Parts: Digital Proximity Sensor (Sharp GP2Y0D02)

The GP2Y0D02 is an infrared proximity sensor with a detection field that extends 80cm. This type of sensor can be used to build collision avoidance systems for robots. We’ll demonstrate this sensor using a single resistor and a multimeter.

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