Nonlinear controllers for floating base systems in contact with the environment are often framed as quadratic programming (QP) optimization problems. Common drawbacks of such QP based controllers are: the friction cone constraints are approximated with a set of linear inequalities; the control input often experiences discontinuities; no force feedback from Force/Torque (FT) sensors installed on the robot is taken into account. This paper attempts at addressing these limitations through the design of jerk controllers. These controllers assume the rate-of-change of the joint torques as control input, and exploit the system position, velocity, accelerations, and contact wrenches as measurable quantities. The key ingredient of the presented approach is a one-to-one correspondence between free variables and the manifold defined by the contact stability constraints. This parametrisation allows us to transform the underlying constrained optimisation problems into one that is unconstrained. Then, we propose a jerk control framework that exploits the proposed parametrisation and uses FT measurements in the control loop. Furthermore, we present Lyapunov stable controllers for the system momentum in the jerk control framework. The approach is validated with simulations and experiments using the iCub humanoid robot.

中文翻译：

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具有接触稳定参数化力反馈的浮动基座系统的加加速度控制

与环境接触的浮动基础系统的非线性控制器通常被定义为二次规划 (QP) 优化问题。这种基于 QP 的控制器的共同缺点是：摩擦锥约束用一组线性不等式逼近；控制输入​​经常出现不连续性；没有考虑安装在机器人上的力/扭矩 (FT) 传感器的力反馈。本文试图通过加加速度控制器的设计来解决这些限制。这些控制器假定关节扭矩的变化率作为控制输入，并利用系统位置、速度、加速度和接触扳手作为可测量量。所提出方法的关键要素是自由变量与由接触稳定性约束定义的流形之间的一一对应关系。这种参数化使我们能够将潜在的受约束优化问题转换为不受约束的优化问题。然后，我们提出了一个 Jerk 控制框架，该框架利用所提出的参数化并在控制回路中使用 FT 测量。此外，我们提出了加加速度控制框架中系统动量的 Lyapunov 稳定控制器。该方法通过使用 iCub 人形机器人的模拟和实验得到验证。我们提出了一个 Jerk 控制框架，它利用了所提出的参数化并在控制回路中使用 FT 测量。此外，我们提出了加加速度控制框架中系统动量的 Lyapunov 稳定控制器。该方法通过使用 iCub 人形机器人的模拟和实验得到验证。我们提出了一个 Jerk 控制框架，它利用了所提出的参数化并在控制回路中使用 FT 测量。此外，我们提出了加加速度控制框架中系统动量的 Lyapunov 稳定控制器。该方法通过使用 iCub 人形机器人的模拟和实验得到验证。