In this paper, we present a framework that unites obstacle avoidance and deliberate physical interaction for robotic manipulators. As humans and robots begin to coexist in work and household environments, pure collision avoidance is insufficient, as human-robot contact is inevitable and, in some situations, desired. Our work enables manipulators to anticipate, detect, and act on contact. To achieve this, we allow limited deviation from the robot's original trajectory through velocity reduction and motion restrictions. Then, if contact occurs, a robot can detect it and maneuver based on a novel dynamic contact thresholding algorithm. The core contribution of this work is dynamic contact thresholding, which allows a manipulator with onboard proximity sensors to track nearby objects and reduce contact forces in anticipation of a collision. Our framework elicits natural behavior during physical human-robot interaction. We evaluate our system on a variety of scenarios using the Franka Emika Panda robot arm; collectively, our results demonstrate that our contribution is not only able to avoid and react on contact, but also anticipate it.
翻译:在本文中,我们提出了一个将机器人操纵者避免障碍和蓄意物理互动结合在一起的框架。当人类和机器人开始在工作和家庭环境中共存时,纯粹避免碰撞是不够的,因为人类-机器人接触是不可避免的,在某些情况下是可取的。我们的工作使操控者能够预见、检测和在接触时采取行动。为了做到这一点,我们允许通过速度降低和动作限制,有限度地偏离机器人最初的轨迹。然后,如果接触发生,机器人可以探测它,并根据新的动态接触阈值算法进行操控。这项工作的核心贡献是动态接触阈值,使机上近距离传感器的操纵者能够跟踪附近物体,并减少预期碰撞时的接触力。我们的框架在人体-机器人互动中产生自然行为。我们利用Franka Emika Panda机器人臂对各种情况进行评估;我们的集体结果表明,我们的贡献不仅能够避免接触和反应,而且能够预测接触。