At present, online lead-through and offline programming methods are widely used in programming of industrial robots. However, both methods have some drawbacks for unskilled shopworkers. This paper presents an Augmented Reality (AR)-based interactive robot teaching programming system, which virtually projected the robot onto the physical industrial environment. The unskilled shopworkers can use Handheld Teaching Device (HTD) to move end-effector of virtual robot to follow endpoint of the HTD. In this way, the path of the virtual robot can be planned or tested interactively. In addition, collisions detection between virtual robot and physical environment is key to test the feasibility of robot path. So, a method for detecting virtual-physical collisions is presented in this paper by comparing the depth values of corresponding pixels in depth image acquired by Kinect and computer-generated image in order to get collision-free paths of the virtual robot. The Quadtree model is used to accelerate the collision detection process and get distance between virtual model and physical environment. Using the AR-based interactive robot teaching programming system presented in this paper, all workers even unskilled ones in robot programming, can quickly and effectively get the collision-free robot path.

目前，在线引导和离线编程方法已广泛用于工业机器人的编程中。但是，这两种方法对于非熟练的车间工人都有一些缺点。本文提出了一种基于增强现实（AR）的交互式机器人教学编程系统，该系统实际上将机器人投影到了物理工业环境中。不熟练的车间工人可以使用手持教学设备（HTD）来移动虚拟机器人的末端执行器，以跟随HTD的端点。通过这种方式，可以交互式地计划或测试虚拟机器人的路径。此外，虚拟机器人与物理环境之间的碰撞检测是测试机器人路径可行性的关键。所以，通过比较Kinect采集的深度图像和计算机生成的图像中相应像素的深度值，提出一种检测虚拟物理碰撞的方法，以获得虚拟机器人的无碰撞路径。Quadtree模型用于加速碰撞检测过程，并获得虚拟模型与物理环境之间的距离。使用本文介绍的基于AR的交互式机器人教学编程系统，所有工人，甚至是不熟练的机器人编程人员，都可以快速有效地获得无碰撞机器人路径。