Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing 100083, People's Republic of China.
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, People's Republic of China.
Philos Trans A Math Phys Eng Sci. 2021 Oct 4;379(2207):20200373. doi: 10.1098/rsta.2020.0373. Epub 2021 Aug 16.
Human-robot collaboration poses many challenges where humans and robots work inside a shared workspace. Robots collaborating with humans indirectly bring difficulties for accomplishing co-carrying tasks. In our work, we focus on co-carrying an object by robots in cooperation with humans using visual and force sensing. A framework using visual and force sensing is proposed for human-robot co-carrying tasks, enabling robots to cooperate with humans and reduce human efforts. Visual sensing for perceiving human motion is involved in admittance-based force control, and a hybrid controller combining visual servoing with force feedback is proposed which generates refined robot motion. The proposed framework is validated by a co-carrying task in experiments. There exist two phases in experimental processes: in , the human hand holds one side of the box object, and the robot gripper of the Baxter robot automatically approaches to the other side of the box object and finally holds it; in , the human and the Baxter robot co-carry the box object over a distance to different target positions. This article is part of the theme issue 'Towards symbiotic autonomous systems'.
人机协作在人类和机器人在共享工作空间中工作的情况下带来了许多挑战。机器人与人类间接协作给共同搬运任务带来了困难。在我们的工作中，我们专注于使用视觉和力觉传感器让机器人与人类协作搬运物体。提出了一个使用视觉和力觉传感器的框架，用于人类机器人共同搬运任务，使机器人能够与人类合作并减轻人类的工作量。基于感知人类运动的视觉感测用于基于导纳的力控制，并且提出了一种结合视觉伺服和力反馈的混合控制器，它生成了更精细的机器人运动。通过实验中的共同搬运任务验证了所提出的框架。实验过程存在两个阶段：在第一阶段，人手握住盒子物体的一侧， Baxter 机器人的机器人夹爪自动靠近盒子物体的另一侧并最终握住它；在第二阶段，人和 Baxter 机器人共同搬运盒子物体经过一段距离到达不同的目标位置。本文是主题为“迈向共生自主系统”的一部分。
