We present a novel haptic teleoperation approach that considers not only the safety but also the stability of a teleoperation system. Specifically, we build upon previous work on haptic shared control, which uses control barrier functions (CBFs) to generate a reference haptic feedback that informs the human operator on the internal state of the system, helping them to safely navigate the robot without taking away their control authority. Crucially, in this approach the force rendered to the user is not directly reflected in the motion of the robot (which is still directly controlled by the user); however, previous work in the area neglected to consider the feedback loop through the user, possibly resulting in unstable closed trajectories. In this paper we introduce a differential constraint on the rendered force that makes the system finite-gain $L_2$ stable; the constraint results in a Quadratically Constrained Quadratic Program (QCQP), for which we provide a closed-form solution. Our constraint is related to but less restrictive than the typical passivity constraint used in previous literature. We conducted an experimental simulation in which a human operator flies a UAV near an obstacle to evaluate the proposed method.
翻译:具体地说,我们以先前关于偶然共享控制的工作为基础,利用控制屏障功能(CBFs)生成参考缓冲反馈,让人类操作者了解系统的内部状态,帮助他们安全驾驶机器人,而不会失去控制权力。 关键是,在这种方法中,给用户的武力没有直接反映在机器人的动作中(机器人仍然直接控制着用户);然而,过去在这一地区的工作忽略了考虑通过用户的反馈循环,这可能导致不稳定的封闭轨迹。 在本文中,我们对使系统定额收益为2美元的定额力施加了差别限制;限制导致一个四重操纵的夸德里亚程序(QCQP),对此我们提供了一种封闭式的解决办法。我们的限制与以往文献中使用的典型的被动度制约有关,但限制较少。我们进行了实验模拟,在这种模拟中,一个人类操作者将UAV公司飞过近一个障碍,以评价拟议方法。