Balancing Drawing Top Robot Patterns

ISEF Category: Technology Enhances the Arts

Subcategory: Engineering Effects  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

A spinning top can be more than a toy. If you control its motion well enough, it can draw clean, repeatable patterns on paper. Your job is to find out when the art stays sharp and when the physics starts to blur it. That mix of motion, control, and image output makes this a strong research project.

What Is It?

This project studies a robot that spins on a single point while an internal sensor system helps keep it upright. The robot carries a brush or pen, so as it spins, it draws a pattern. If the timing and balance are tuned well, the line path can form a Lissajous pattern, which is a looping shape made by combining two smooth motions at right angles.

Think of it like a dancer drawing with their feet while trying not to fall. The robot has to manage rotation, balance, and contact with the page at the same time. The IMU, short for inertial measurement unit, acts like the robot's inner ear. It measures tilt and motion, so the controller can make small corrections while the top slows down.

Why This Is a Good Topic

This is a strong science fair topic because you can test it with real measurements. You can compare drawing quality, spin-rate decay, and control settings across trials, then look for patterns in the data. The project connects to robotics, control systems, and creative technology, so it has a clear engineering story. You can also learn image analysis, signal tracking, and experimental design without needing a biology-style wet lab.

Research Questions

• How does initial spin rate affect the fidelity of the drawn Lissajous pattern?
• What is the effect of brush pressure on pattern clarity and line continuity?
• Does IMU control tuning change how long the robot maintains a recognizable pattern?
• To what extent does paper surface texture affect line symmetry and pattern distortion?
• Which spin-rate decay threshold marks the point where pattern fidelity drops below a useful level?
• How does battery voltage during a run affect drawing stability and repeatability?

Basic Materials

• Microcontroller board with IMU support, such as an Arduino or ESP32 system.
• IMU sensor module for tilt and motion tracking.
• Small brushed or brushless motor with mounting hardware.
• Stable single-point bearing or tip assembly for spinning support.
• Pen, brush, or marker mount with adjustable contact pressure.
• Plain drawing paper and backup paper sheets.
• Digital kitchen scale for balancing parts.
• Smartphone camera or tripod-mounted camera for recording trials.
• Ruler, calipers, and tape for alignment checks.
• Notebook or spreadsheet for logging trial settings and results.

Advanced Materials

• High-resolution IMU module with logged acceleration and gyro data.
• Data acquisition board or microcontroller with stable sampling.
• Custom 3D-printed chassis and brush mount.
• Precision bearings or low-friction pivot hardware.
• Optical tachometer or encoder for spin-rate measurement.
• Force sensor or load cell for brush contact force testing.
• Computer with image analysis software for line tracking.
• Test paper with controlled surface finish or coated samples.
• Oscilloscope for motor drive signal inspection.
• Power supply with monitored output stability.

Software & Tools

• ImageJ: Measures line width, symmetry, and pattern overlap from photographed drawings.
• Python: Helps you process spin data, compute error metrics, and graph trends.
• Tracker: Lets you inspect motion paths and compare drawing geometry frame by frame.
• GeoGebra: Helps you model ideal Lissajous curves and compare them to your results.
• Google Sheets: Organizes trials, calculates averages, and plots pattern fidelity against spin decay.

Experiment Steps

1. Define the one output you will score, such as pattern symmetry, line continuity, or curve error.
2. Choose the control variable you will change first, such as spin rate, brush force, or controller gain.
3. Plan a repeatable way to capture both the drawing and the motion data in the same trial.
4. Build a scoring method that turns each drawing into numbers you can compare across runs.
5. Set up control trials that separate mechanical drift from sensor or software effects.
6. Map out how you will test whether pattern quality falls at the same time spin rate decays.

Common Pitfalls

• Letting the brush contact force change from trial to trial, which makes pattern differences hard to attribute.
• Using uneven paper or a shifting paper mount, which distorts the drawing even when the robot behaves the same.
• Recording drawings under changing light or camera angle, which breaks image analysis and makes line measurements unreliable.
• Ignoring motor warm-up or battery drop, which changes spin decay and confuses the control results.
• Treating the ideal curve as the only metric, which misses useful errors like line jitter, drift, and self-intersection.

What Makes This Competitive

A stronger project goes beyond a cool robot demo. You can compare multiple control strategies, define a clear fidelity metric, and test whether the robot fails in the same way across materials or settings. If you connect motion data to the final artwork with a clean statistical model, your results look much more serious. A novel angle, such as quantifying when artistic shape starts to collapse, can make the project stand out.

Project Variations

• Test how different brush tips, such as felt, fiber, or gel, change line fidelity and decay behavior.
• Compare paper types, such as smooth sketch paper, cardstock, and coated paper, to see how surface friction affects pattern quality.
• Swap Lissajous curves for other parametric shapes, such as spirals or rose curves, and measure which ones survive spin decay best.

Learn More

• MIT OpenCourseWare: Search for intro materials on feedback control, robotics, and motion systems.
• NASA: Use engineering and systems articles to study sensors, stability, and closed-loop control.
• NIH PubMed: Search for review articles on IMU-based motion tracking and signal filtering methods.
• ImageJ documentation: Learn how to measure line width, shape overlap, and image contrast from your drawings.
• IEEE Xplore: Search for papers on self-balancing robots, pen plotters, and drawing mechanisms to compare methods.