In order to be effective partners for humans, robots must become increasingly comfortable with making contact with their environment. Unfortunately, it is hard for robots to distinguish between ``just enough'' and ``too much'' force: some force is required to accomplish the task but too much might damage equipment or injure humans. Traditional approaches to designing compliant force-feedback controllers, such as stiffness control, require difficult hand-tuning of control parameters and make it difficult to build safe, effective robot collaborators. In this paper, we propose a novel yet easy-to-implement force feedback controller that uses control barrier functions (CBFs) to derive a compliant controller directly from users' specifications of the maximum allowable forces and torques. We compare our approach to traditional stiffness control to demonstrate potential advantages of our control architecture, and we demonstrate the effectiveness of our controller on an example human-robot collaboration task: cooperative manipulation of a bulky object.
翻译:为了成为人类的有效伙伴,机器人必须越来越乐于与环境接触。 不幸的是,机器人很难区分“足够”和“太多”的力量:需要一些力量来完成任务,但可能会损害设备或伤害人。设计守法的“部队支架控制器”的传统方法,如僵硬控制,要求难以对控制参数进行手调,并难以建立安全有效的机器人合作者。在本文件中,我们提议建立一个使用控制屏障功能(CBFs)的新型但易于执行的反馈控制器,直接从用户对最大允许力和托鲁斯的规格中获取一个符合要求的控制器。我们将我们的方法与传统的僵硬控制方法进行比较,以展示我们控制结构的潜在优势,并展示我们的控制器在人类机器人合作任务上的有效性:合作操纵一个大宗物体。