论文标题
通过风险敏感的最佳控制，用于不确定接触互动的阻抗优化
Impedance Optimization for Uncertain Contact Interactions Through Risk Sensitive Optimal Control
论文作者
论文摘要
本文解决了计算涉及复杂接触互动的腿部运动任务的最佳阻抗时间表的问题。我们将阻抗调节的问题提出，作为干扰排斥和测量不确定性之间的权衡。我们扩展了一种称为风险敏感控制的随机最佳控制算法，以考虑测量不确定性，并提出一种形式的方式，以包括未知接触位置的这种不确定性。该方法可以有效地生成最佳状态和控制轨迹以及本地反馈控制收益，即阻抗时间表。广泛的模拟证明了该方法在接触相互作用之前和之后产生有意义的刚度和阻尼调制模式的能力。例如，在早期接触期间，接触力减少，阻尼增加以预测高影响事件，并且跟踪自动交易以提高稳定性。特别是，我们通过模拟的四足机器人在跳跃和小跑任务期间的性能有了显着改善。
This paper addresses the problem of computing optimal impedance schedules for legged locomotion tasks involving complex contact interactions. We formulate the problem of impedance regulation as a trade-off between disturbance rejection and measurement uncertainty. We extend a stochastic optimal control algorithm known as Risk Sensitive Control to take into account measurement uncertainty and propose a formal way to include such uncertainty for unknown contact locations. The approach can efficiently generate optimal state and control trajectories along with local feedback control gains, i.e. impedance schedules. Extensive simulations demonstrate the capabilities of the approach in generating meaningful stiffness and damping modulation patterns before and after contact interaction. For example, contact forces are reduced during early contacts, damping increases to anticipate a high impact event and tracking is automatically traded-off for increased stability. In particular, we show a significant improvement in performance during jumping and trotting tasks with a simulated quadruped robot.
