Extended Version of GTGraffiti: Spray Painting Graffiti Art from Human Painting Motions with a Cable Driven Parallel Robot

TL;DR

This paper introduces GTGraffiti, a system that captures human graffiti motions and reproduces them with a cable-driven robot, enabling realistic graffiti art creation with high fidelity and dynamic motion.

Contribution

The paper presents a novel integrated system combining motion capture, custom hardware, and control algorithms to replicate human graffiti motions with a cable-driven parallel robot.

Findings

Reproduces artist motions up to 2m/s speed

Achieves 9.3mm RMSE in painting accuracy

Demonstrates faithful recreation of graffiti art

Abstract

We present GTGraffiti, a graffiti painting system from Georgia Tech that tackles challenges in art, hardware, and human-robot collaboration. The problem of painting graffiti in a human style is particularly challenging and requires a system-level approach because the robotics and art must be designed around each other. The robot must be highly dynamic over a large workspace while the artist must work within the robot's limitations. Our approach consists of three stages: artwork capture, robot hardware, and planning & control. We use motion capture to capture collaborator painting motions which are then composed and processed into a time-varying linear feedback controller for a cable-driven parallel robot (CDPR) to execute. In this work, we will describe the capturing process, the design and construction of a purpose-built CDPR, and the software for turning an artist's vision into control commands. Our work represents an important step towards faithfully recreating human graffiti artwork by demonstrating that we can reproduce artist motions up to 2m/s and 20m/s$^2$ within 9.3mm RMSE to paint artworks. Changes to the submitted manuscript are colored in blue.