01 / OVERVIEW
Turning a mechanical toy into a mechatronic drawing machine
The Etch A Sketch Drawing Robot started as a personal challenge: take a simple mechanical toy and convert it into an automated drawing machine. Instead of treating it only as a fun video idea, I approached it as a complete mechatronics project involving mechanical design, actuation, electronics, software logic, calibration and testing. The goal was to make the toy draw recognizable images automatically while documenting the process as public engineering content.
02 / ENGINEERING CHALLENGE
Controlling an imprecise physical mechanism
The main challenge was that an Etch A Sketch is not designed to be a precise robotic system. It has mechanical backlash, friction, limited resolution, knob coupling constraints and nonlinear behavior caused by the internal drawing mechanism. To create useful drawings, the system needed to translate digital motion commands into physical knob rotation while compensating for imperfections through calibration, mechanical mounting and iterative testing.
03 / MECHANICAL DESIGN
Designing a motorized frame around an existing toy
I designed the mechanical layout in SolidWorks to hold the Etch A Sketch and align the motors with the two drawing knobs. The design had to be simple, rigid and adjustable enough to deal with the geometry of the toy. The motor mounts, coupling approach and frame layout were developed to transmit rotation reliably while keeping the system easy to assemble, test and modify.
04 / ELECTRONICS & CONTROL
Integrating stepper motors and controller hardware
The actuation system used stepper motors to control the horizontal and vertical drawing axes. I integrated the motors with driver electronics and a Raspberry Pi-based control setup, then developed the motion logic required to coordinate both axes. The system had to convert drawing commands into step sequences while accounting for direction changes, speed limits and the physical response of the toy.
05 / CALIBRATION & TESTING
Turning digital images into drawable trajectories
To convert an input image into a path that the Etch A Sketch could physically reproduce, I developed an image-processing and path-planning pipeline. A Canny edge detector was first used to extract the main contours of the image and convert them into a set of drawable points. A Traveling Salesman Problem (TSP)-based optimization was then used to order and connect these points, reducing unnecessary movement and generating an efficient trajectory for the drawing mechanism.
The resulting path was translated into coordinated X-Y motion commands for the two stepper motors, connecting image processing directly with the physical behavior of the machine. This allowed the robot to transform ordinary digital images into simplified line drawings that could be recreated on the Etch A Sketch.
06 / ENGINEERING COMMUNICATION
Documenting the build for YouTube and TikTok
A major part of the project was communicating the engineering process to a public audience. Through YouTube and TikTok, I documented the design, build, testing, and final result while explaining the reasoning behind the mechanical, electronic, and software decisions made throughout the project. This required translating technical concepts into a clear visual narrative without losing the engineering logic behind the system.
Documenting the development turned the project into a clear sequence of problems, iterations and solutions, from motor-interface design and electronics integration to motion calibration and image-to-drawing conversion. For me, it captures why I enjoy engineering communication: showing not only the final prototype, but also the decisions and adjustments required to make it work.
07 / OUTCOME
A functional prototype with public storytelling value
What this project demonstrates
• Personal mechatronic prototyping
• Mechanical design around existing hardware
• Stepper motor integration
• Controller hardware integration
• Motion-control logic
• Calibration of imperfect mechanisms
• Iterative physical testing
• Troubleshooting backlash and friction
• Engineering communication through
• YouTube and TikTok
• Turning a playful idea into a functional prototype
• Image processing using Canny edge detection
• TSP-based trajectory optimization
Image gallery
FINAL PROTOTYPE
FINAL DRAWING