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.
翻译:我们介绍GTGGraffiti, Georgia Tech 的涂鸦绘画系统, 解决艺术、 硬件和人类机器人合作的挑战。 以人文风格涂鸦的问题特别具有挑战性, 需要系统层面的方法, 因为机器人和艺术必须互相设计。 机器人必须在大型工作空间高度动态, 而艺术家必须在机器人的限度内工作。 我们的方法包括三个阶段: 艺术品捕获、 机器人硬件以及规划与控制。 我们用运动捕捉捕捕捕捉来捕捉合作者绘画的动作, 这些动作随后组成并处理成一个时间变化的线性线性反馈控制器, 用于一个由电缆驱动的平行机器人( CDPR) 执行。 在这项工作中, 我们将描述捕捉过程、 设计与建造目的的CDPR 以及将艺术家的视觉变成控制指令的软件。 我们的工作代表了忠实地重建人类涂鸦画艺术的重要一步, 展示我们可以将艺术家的作品复制到每秒2m/ s和20m/s$2$9mm RMSE 在9.3mm RMS 内制作艺术作品。 。 对提交的手稿的修改是蓝色的颜色。 。