Planet Arduino

Ping pong is one of the most popular sports in the world, but that doesn’t mean that it is easy to find people to practice with. Lone players are typically forced to practice by using return boards (or one half of the table flipped up), but that is overly predictable. To provide a better training experience, BINGOBRICKS designed this ping pong robot that serves balls according to user preferences.

This is a bit like a tennis ball serving machine, but tailored to the particular quirks of ping pong. Through a control panel on the back of the robot, the user can set the serve parameters. Those include the direction of the serve and even the spin of the ball — anywhere from a full top spin to a full back spin. A quick launch tube swap lets the user switch between high ball releases or low ball releases. To keep the player on their toes, the machine can release balls in different directions throughout a session.

Most of the robot’s body and mechanical parts are 3D-printable. An Arduino Nano board controls the motors according to the parameters set by the switches and dials. Potentiometers allow adjustment for the intervals between serves, speed, and spin, while three toggle switches control the directions in which the robot will serve balls. A servo motor controls the angle of the launch tube, a pair of DC motors spin the launch wheels (their relative speed sets the ball spin), and another DC motor rotates the hopper’s feed arm.

The post Ping pong robot lets you dial-in the serves appeared first on Arduino Blog.

Shortly after the COVID-19 pandemic began, Samuel Alexander and his housemates purchased a ping pong set and began to play — a lot. Becoming quite good at the game, Alexander realized that his style was not consistent with how more professional table tennis players hit the ball, as he simply taught himself without a coach. Because of this, he was inspired to create a smart paddle that uses an integrated IMU to intelligently classify which moves he makes and correct his form to improve it over time. 

Alexander went with the Nano 33 BLE Sense board due to its ease of use and tight integration with TensorFlow Lite Micro, not to mention the onboard 6DOF accelerometer/ gyroscope module. He began by designing a small cap that fits over the bottom of a paddle’s handle and contains all the electronics and battery circuitry. With the hardware completed, it was time to get started with the software.

The Tiny Motion Trainer by Google Creative Lab was employed to quickly capture data from the Arduino over Bluetooth and store the samples for each motion. Once all of the movements had been gathered, Alexander trained the model for around 90 epochs and was able to achieve an impressive level of accuracy. His build log and demonstration video below shows how this smart paddle can be used to intelligently classify and coach a novice player into using better form while playing, and it will be fun to see just how good the model can get. 

The post Meet your new table tennis coach, a tinyML-powered paddle! appeared first on Arduino Blog.

Friction wheel mechanism, frame made of VEX Robotics Design System components.

Read more on MAKE