Variable Horizon MPC With Swing Foot Dynamics for Bipedal Walking Control
Variable Horizon MPC With Swing Foot Dynamics for Bipedal Walking Control
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DOI：
10.1109/lra.2021.3061381
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发表时间：
2021-04-01
影响因子：
5.2
通讯作者：
Righetti, Ludovic
中科院分区：
文献类型：
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作者：
Daneshmand, Elham;Khadiv, Majid;Righetti, Ludovic
在这封信中，我们提出了一种新的两足运动两级变视野模型预测控制(VH-MPC)框架。在该框架中，较高级别使用来自重心(COM)状态的反馈来计算摆动脚的着陆位置和定时(地平线长度)以稳定重心(COM)动力学的不稳定部分。下层考虑了摆动脚的动力学，并生成动态一致的轨迹，以便在尽可能接近所需位置的所需时间着陆。为此，我们使用了一个简化的机器人动力学模型，该模型考虑了关节扭矩约束以及站立脚的摩擦锥约束。我们通过在我们的扭矩控制的开源双足机器人Bolt上实现健壮的行走模式来展示我们所提出的控制框架的有效性。我们报告了在存在各种干扰和不确定性的情况下进行的广泛的仿真和真实的机器人实验。
In this letter, we present a novel two-level variable Horizon Model Predictive Control (VH-MPC) framework for bipedal locomotion. In this framework, the higher level computes the landing location and timing (horizon length) of the swing foot to stabilize the unstable part of the center of mass (CoM) dynamics, using feedback from the CoM states. The lower level takes into account the swing foot dynamics and generates dynamically consistent trajectories for landing at the desired time as close as possible to the desired location. To do that, we use a simplified model of the robot dynamics projected in swing foot space that takes into account joint torque constraints as well as the friction cone constraints of the stance foot. We show the effectiveness of our proposed control framework by implementing robust walking patterns on our torque-controlled and open-source biped robot, Bolt. We report extensive simulations and real robot experiments in the presence of various disturbances and uncertainties.