论文标题
基于激光的双臂系统，用于精确控制协作机器人
A Laser-based Dual-arm System for Precise Control of Collaborative Robots
论文作者
论文摘要
协作机器人以相对较低的成本提供了提高的交互功能，但与其工业相比，它们不可避免地缺乏精确度。此外，除了机器人自己的不完美模型外，日常操作还需要各种错误来源，尽管迅速积累了这些错误。当任务更改和机器人被重新编程时发生，通常需要耗时的校准。这些方面强烈限制了协作机器人在要求高精度（例如制表）任务中的应用。我们通过依靠具有激光感应的双臂系统来解决这个问题，以衡量感兴趣的对象之间的相对姿势，并补偿来自机器人本体感受的姿势错误。我们的方法利用对象3D模型的先前知识与点云注册相结合，以有效提取相关姿势并计算纠正轨迹。这会导致高精度组装行为。该方法在针线螺纹实验中进行了验证，具有150μm线和300μm孔以及使用两个7轴熊猫机器人的USB插入任务。
Collaborative robots offer increased interaction capabilities at relatively low cost but in contrast to their industrial counterparts they inevitably lack precision. Moreover, in addition to the robots' own imperfect models, day-to-day operations entail various sources of errors that despite being small rapidly accumulate. This happens as tasks change and robots are re-programmed, often requiring time-consuming calibrations. These aspects strongly limit the application of collaborative robots in tasks demanding high precision (e.g. watch-making). We address this problem by relying on a dual-arm system with laser-based sensing to measure relative poses between objects of interest and compensate for pose errors coming from robot proprioception. Our approach leverages previous knowledge of object 3D models in combination with point cloud registration to efficiently extract relevant poses and compute corrective trajectories. This results in high-precision assembly behaviors. The approach is validated in a needle threading experiment, with a 150μm thread and a 300μm hole, and a USB insertion task using two 7-axis Panda robots.
