Who wouldn’t want a robot that can fetch them a glass of water? [Saral Tayal] didn’t just think that, he jumped right in and built his own personal assistant robot. This isn’t just some remote-controlled rover though. The robot actually listens to his voice and recognizes his face.
The body of the robot is the common “Rover 5” platform, to which [Saral] added a number of 3D printed parts. A forklift like sled gives the robot the ability to pick things up. Some of the parts are more about form than function – [Saral] loves NASA’s Spirit and Opportunity Mars rovers, so he added some simulated solar cells and other greebles.
The Logitech webcam up front is very functional — images are fed to machine learning models, while audio is processed to listen for commands. This robot can find and pick up 90 unique objects.
The robot’s brains are a Raspberry Pi. It uses TensorFlow for object recognition. Some of the models [Saral] is using are pretty large – so big that the Pi could only manage a couple of frames per second at 100% CPU utilization. A Google Coral coprocessor sped things up quite a bit, while only using about 30% of the Pi’s processor.
It takes several motors to control to robot’s tracks and sled. This is handled by two Roboclaw motor controllers which themselves are commanded by the Pi.
We’ve seen quite a few mobile robot rovers over the years, but [Saral’s] ‘bot is one of the most functional designs out there. Even better is the fact that it is completely open source. You can find the code and 3D models on his GitHub repo.
Check out a video of the personal assistant rover in action after the break.
Continue reading “DIY Personal Assistant Robot Hears And Sees All”
Social media can connect us to a vibrant worldwide community, but it is also a huge time sink as it preys on both our need for attention and our insatiable curiosity. Kept on a leash by those constant notification sounds, we can easily look up from our phones to find half a day has gone and we’re behind with our work. [Laura Lytle] has a plan to tackle this problem, her OutBox project involves a single button press machine that posts a picture to Twitter of whatever is put in it. It’s not just another gateway to social media addiction though, she tells us it follows Design For Disuse principles in which it must be powered up and adjusted for each picture, and that it provides no feedback to satisfy the social media craving.
Under the hood of the laser-cut housing reminiscent of an older hobby 3D printer is a Raspberry Pi 3 Model A+ and a webcam, with a ring of LEDs for illumination. On top is the only interface, a small “arm” button to set things up and a big red arcade button to do the business. The software is in Python, and provides glue between resizing the photo, uploading it to a cloud service, and triggering ITTT to do the Tweeting. You can see the whole thing in the video below, and the result is a rather eye-catching device.
Of course, there are other ways to keep yourself off social media.
Continue reading “Be On Twitter Without Being On Twitter”
Finally, a useful application for machine vision! Forget all that self-driving nonsense and facial recognition stuff – we’ve finally got an AI that can count cards at the blackjack table.
The system that [Edje Electronics] has built, dubbed “Rain Man 2.0” in homage to the classic title character created by [Dustin Hoffman] for the 1988 film, aims to tilt the odds at the blackjack table away from the house by counting cards. He explains one such strategy, a hi-low count, in the video below, which Rain Man 2.0 implements with the help of a webcam and YOLO for real-time object detection. Cards are detected in any orientation based on their suit and rank thanks to an extensive training set of card images, which [Edje] generated synthetically via some trickery with OpenCV. A script automated the process and yielded a rich training set of 50,000 images for YOLO. A Python program implements the trained model into a real-time card counting application.
Rain Man 2.0 is an improvement over [Edje]’s earlier Tensor Flow card counter, but it still has limitations. It can’t count into a six-deck shoe as the fictional [Rain Man] could, at least not yet. And even though cheater’s justice probably isn’t all cattle prods and hammers these days, the hardware needed for this hack is not likely to slip past casino security. So [Edje] has wisely limited its use to practicing his card counting skills. Eventually, he wants to turn Rain Man into a complete AI blackjack player, and explore its potential for other games and to help the visually impaired.
Continue reading “Let The Cards Fall Where They May, With A Robotic Rain Man”
The Rubik’s Cube was a smash hit when it came out in 1974, and continues to maintain a following to this day. It can be difficult to solve, but many take up the challenge. The Arduino Rubik’s Solver is a robot that uses electronics and maths to get the job done.
The system consists of computer-based software and a hardware system working in concert to solve the cube. Webcam images are processed on a computer which determines the current state of the cube, and the necessary moves required to solve it. The solving rig is constructed from steel rods, lasercut acrylic, and 3D printed parts, along with an Arduino and six stepper motors. The Arduino receives instructions from the solving computer over USB serial link. These are then used to command the stepper motors to manipulate the cube in the correct fashion.
It’s no speed demon, but the contraption is capable of solving a cube without any problems. Manipulation of the cube is reliable and smooth, and the build is neat and tidy thanks to its carefully designed components. Of course, there are now even Rubik’s Cubes that can solve themselves. Video after the break.
Continue reading “Yet Another Robotic Rubik’s Solver”
[Mark West] gave an interesting presentation at last year’s GOTO Copenhagen conference. He shows how he took a simple Raspberry Pi Zero webcam and expanded it with AI. He actually added the intelligent features in two different ways: on in the Amazon cloud and another using the Intel Modvidius NCS USB stick directly connected to the USB. You can see the video below.
Local motion detection uses some open source software. You simply configure it using a text file and it even handles the video streaming. However, at that point, you just have a web camera — not amazing, nor very cost effective. However, you get a lot of false alarms with the motion detection software. A random cat walking past, clouds, trees, or even rain would push [Mark] an email and after 250 alert e-mails a day, [Mark] decided to make something better.
Continue reading “Raspberry Pi Camera With Smarts — Cloud Or Local?”
If IKEA made ball-balancing PID robots, they’d probably look like this one.
This [Johan Link] build isn’t just about style. A look under the hood reveals not the standard, off-the-shelf microcontroller development board you might expect. Instead, [Johan] designed and built his own board with an ATmega32 to run the three servos that control the platform. The entire apparatus is made from a dozen or so 3D-printed parts that interlock to form the base, the platform, and the housing for the USB webcam that’s perched on an aluminum tube. From that vantage point, the camera’s images are analyzed with OpenCV and the center of the ball is located. A PID loop controls the three servos to center the ball on the platform, or razzle-dazzle it a little by moving the ball in a controlled circle. It’s quite a build, and the video below shows it in action.
We’ve seen a few balancing platforms before, but few with such style. This Stewart platform comes close, and this juggling platform gets extra points for closing the control loop with audio feedback. And for juggling, of course.
Continue reading “High-Style Ball Balancing Platform”
Looking for a cheap way to keep an eye on something? [Kevin Hester] pointed us to a way to make a WiFi webcam for under $10. This uses one of the many cheap ESP32 dev boards available, along with the Internet of Things platform PlatformIO and a bit of code that creates an RTSP server. This can be accessed by any software that supports this streaming protocol, and a bit of smart routing could put it on the interwebs. [Kevin] claims that the ESP32 camera dev boards he uses can be found for less than $10, but we found that most of them cost about $15. Either way, that’s cheaper than most commercial streaming cameras.
Continue reading “Cheap ESP32 Webcam”