用AR扫描工位，快速优化机器人放置位置
RobotGraffiti: An AR tool for semi-automated construction of workcell models to optimize robot deployment
- 通过手机扫描+AR界面收集工位数据，自动推荐最优机器人基座位置
- 相比传统方法，部署时间最多缩短16倍
- 适合制造业工程师快速部署机器人，无需复杂建模
提升机器人部署效率是加速制造自动化的核心步骤。主要挑战在于如何最优地布置机器人在工位中的位置。本文结合系统级机器人知识与用户对工位环境的认知，通过增强现实（AR）界面实现二者融合。RobotGraffiti是一款独特工具，使用户能通过移动设备完成工位3D扫描，补充系统难以推断的上下文信息，并获得满足自动化任务的机器人基座位置建议。该方法替代了昂贵且耗时的数字孪生，提供一种快速、易用的工具，聚焦于运行放置优化算法所需的特定工位特征。本文主要贡献包括新颖的机器人基座位置数据采集用户界面，以及传统离线仿真与本方法的对比研究。通过实例展示，可实现最高16倍的时间节约。
原文摘要 · Abstract (English)
Improving robot deployment is a central step towards speeding up robot-based automation in manufacturing. A main challenge in robot deployment is how to best place the robot within the workcell. To tackle this challenge, we combine two knowledge sources: robotic knowledge of the system and workcell context awareness of the user, and intersect them with an Augmented Reality interface. RobotGraffiti is a unique tool that empowers the user in robot deployment tasks. One simply takes a 3D scan of the workcell with their mobile device, adds contextual data points that otherwise would be difficult to infer from the system, and receives a robot base position that satisfies the automation task. The proposed approach is an alternative to expensive and time-consuming digital twins, with a fast and easy-to-use tool that focuses on selected workcell features needed to run the placement optimization algorithm. The main contributions of this paper are the novel user interface for robot base placement data collection and a study comparing the traditional offline simulation with our proposed method. We showcase the method with a robot base placement solution and obtain up to 16 times reduction in time.
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