论文标题
使用力，扭矩和RGB-D传感的自动工业集会
Autonomous Industrial Assembly using Force, Torque, and RGB-D sensing
论文作者
论文摘要
我们为机器人操纵系统提供了算法和结果，该系统旨在易于编程和适应工业环境所共有的各种任务，该任务是受到东京2018年世界机器人峰会的工业集会挑战的启发。这项挑战包括将标准，可商购的工业零件组装成2D和3D组件。我们演示了三个任务，可以将其分类为“钉孔”和“孔洞”任务，并识别两种规范算法：基于螺旋的搜索和倾斜插入。两种算法都使用力和扭矩域中的手动编码阈值来检测组件中的临界点。在简要概述了研究中的最新技术状态之后，我们描述了测试系统使用的策略和方法，其设计如何遵循其性能，每项任务的20个实验试验的统计数据，在系统开发过程中汲取的经验教训以及仍然存在的开放研究挑战。
We present algorithms and results for a robotic manipulation system that was designed to be easily programmable and adaptable to various tasks common to industrial setting, which is inspired by the Industrial Assembly Challenge at the 2018 World Robotics Summit in Tokyo. This challenge included assembly of standard, commercially available industrial parts into 2D and 3D assemblies. We demonstrate three tasks that can be classified into "peg-in-hole" and "hole-on-peg" tasks and identify two canonical algorithms: spiral-based search and tilting insertion. Both algorithms use hand-coded thresholds in the force and torque domains to detect critical points in the assembly. After briefly summarizing the state of the art in research, we describe the strategy and approach utilized by the tested system, how it's design bears on its performance, statistics on 20 experimental trials for each task, lessons learned during the development of the system, and open research challenges that still remain.
