Planet Arduino

At this point, society has had over three decades to get used to the Blue Man Group. Maybe that’s why we’re less disturbed by [Graham Jessup]’s face-tracking Watchman than we should be. Either that, or it’s because it reminds us of Data from Star Trek: The Next Generation. Frankly, this is just way too cool to be dismissed out of hand as creepy.

The Watchman finds faces via video feed from a camera module positioned in his forehead as a third eye. The camera is connected to a Pi Zero that’s wearing a Google AIY vision bonnet. The Pi translates the face locations into servo positions and feeds them to an Arduino UNO located in the frontal lobe region to move the eyeballs and lids accordingly.

[Graham] had a bit of trouble with tracking accuracy at first, so he temporarily replaced the pupils with 5 mW lasers and calibrated them by tracking a printed stand-in of his head to avoid burning out his retinas.

This project builds on previous work by [Tjahzi] and the animatronic eye movements of [Will Cogley]. We can only imagine how awesome the Watchman would look with a pair of [Will]’s incredibly realistic eyeballs. Either way, we would totally trust the Watchman to defend our modest supply of toilet paper in the coming weeks. Check out a brief demo after the break, and a whole lot more clips on [Graham]’s site.

Via reddit

When you step out in public, you’ll often be filmed by a number of cameras and perhaps even be analyzed by tracking software of some kind. The Watchman robot head by Graham Jessup, however, makes this incredibly obvious as it detects and recognizes facial movements, then causes a pair of eyeballs to follow you around.

The 3D-printed system — which is a modified version of Tjhazi’s Doorman — uses a Raspberry Pi Camera to capture a live video feed, along with a Raspberry Pi Zero and a Google AIY HAT for analysis.

This setup passes info on to an Arduino Uno that actuates the eyeballs via a 16-channel servo shield and a number of servos. The device can follow Jessup up, down, left, and right, making for a very creepy robot indeed!

Computer vision has traditionally relied on an assortment of rather involved components. On the other hand, everything you need to do this complicated task is readily available on an Android phone. The clever setup seen in the video here uses a smartphone to capture and process images, then send out a signal over Bluetooth to tell which way the device needs to be adjusted in order to focus on a nearby face.

An HC-05 Bluetooth module receives this signal and passes it to two servo motors via an Arduino Nano, moving the phone left/right and up/down.

You can find the Arduino code for this project on CircuitDigest, and the Android Processing code can be downloaded there as a compressed folder.

[Sergey Mironov] sent in his SelfieBot project. His company, Endurance Robots, sells a commercial version of the bot, which leads us to believe that in a strange and maybe brilliant move he decided to just sell the prototype stage of the product development as a kit. Since he also gave away the firmware, STLs, BOM, and made a guide so anyone can build it, we’re not complaining.

The bot is simple enough. Nicely housed hobby servos in a 3D printed case take care of the pan and tilt of the camera. The base of the bot encloses the electronics, which are an Arduino nano, a Bluetooth module, and the support electronics for power and motor driving.

To perform the face tracking, the build assumes you have a second phone. This is silly, but isn’t so unreasonable. Most people who’ve had a smart phone for a few years have a spare one living in a drawer as back-up. One phone runs the face tracking software and points the bot, via Bluetooth, towards the user. The other phone records the video.

The bot is pretty jumpy in the example video, but this can be taken care of with better motors. For a proof-of-concept, it works. A video of it in action after the break.

A team of mechanical and electrical engineering students at Olin College came up with a very fun semester project — a pneumatic powered marshmallow cannon that can track faces, and aim for the mouth!

The device — dubbed the Confectionery Canon — is an impressive mechanical build which required many of Olin College’s manufacturing resources such as the laser cutter, the mill, and the lathe. The majority of the device was made out of acrylic, which was chosen for easy laser cutting, and affordability. Specific aluminum pieces provide strength and were made using mostly scrap found in the shop.

Four servos, a webcam, a solenoid and an Arduino Uno make up the electrical system, which uses Python and OpenCV to track faces (GitHub). A PVC tank is used as the pneumatic reservoir, charged with a safety release valve at 30PSI. To fire the cannon, a sprinkler valve is controlled by a beefy solenoid. It currently only has a magazine capacity of 4 large marshmallows, but the team is planning on upgrading soon.

They have put together a great website with tons of information on the project, and following the break is a fun promo video they made for the project — they even got the VP of  the college to try it!

In case you haven’t been counting, we’ve shared over a dozen projects that have come out of Olin College — and they are all awesome. A CNC cake decorator, a Wii-mote controlled go kart, a machine that hand writes for you…