Robot

Process (computing)

Biology

Computer graphics (images)

Operating system

Computer science

Visual arts

Controller (irrigation)

Agronomy

Graffiti

Robotics

Artificial intelligence

Painting

Workspace

Computer vision

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 systemlevel 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.

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