The automation of key processes in metal cutting would substantially benefit many industries such as manufacturing and metal recycling. We present a vision-based control scheme for automated metal cutting with oxy-fuel torches, an established cutting medium in industry. The system consists of a robot equipped with a cutting torch and an eye-in-hand camera observing the scene behind a tinted visor. We develop a vision-based control algorithm to servo the torch's motion by visually observing its effects on the metal surface. As such, the vision system processes the metal surface's heat pool and computes its associated features, specifically pool convexity and intensity, which are then used for control. The operating conditions of the control problem are defined within which the stability is proven. In addition, metal cutting experiments are performed using a physical 1-DOF robot and oxy-fuel cutting equipment. Our results demonstrate the successful cutting of metal plates across three different plate thicknesses, relying purely on visual information without a priori knowledge of the thicknesses.

翻译：摘要：金属切割关键过程的自动化将极大惠及制造业及金属回收等众多行业。本文提出了一种基于视觉的自动化金属切割控制方案，采用工业中成熟的气割炬作为切割介质。该系统由配备切割炬的机器人以及安装在机械臂上的摄像头组成，该摄像头透过有色防护镜观察切割场景。我们开发了一种基于视觉的控制算法，通过观察金属表面的变化来伺服控制切割炬的运动。具体而言，视觉系统处理金属表面的热熔池，并计算其相关特征——特别是熔池的凸度与强度，并将这些特征用于控制。我们定义了控制问题的运行条件，并证明了在此条件下的系统稳定性。此外，我们使用单自由度物理机器人及气割设备进行了金属切割实验。实验结果表明，仅凭视觉信息（无需预先获知板材厚度），系统即可成功切割三种不同厚度的金属板材。