论文标题
非线性模型的基于优化的参考生成器对腿机器人的预测控制
Optimization-Based Reference Generator for Nonlinear Model Predictive Control of Legged Robots
论文作者
论文摘要
模型预测控制（MPC）方法被广泛用于机器人技术，因为它们可以保证可行性并允许在机器人移动时计算更新的轨迹。他们通常需要启发式参考，以进行跟踪术语和成本函数参数的正确调整，以便获得良好的性能。例如，当腿部机器人必须应对环境的干扰（例如，推动后恢复）或跟踪具有静态不稳定步态的特定目标时，算法的有效性可能会降解。在这项工作中，我们提出了一种基于优化的参考生成器，该发电机利用线性的倒摆（LIP）模型来计算质量中心的参考轨迹，同时考虑了步态的可能不足（例如，在小跑中）。所获得的轨迹用作我们以前工作中介绍的非线性MPC成本函数的参考。我们还提出了一种表述，以确保响应时间保证达到目标，而无需调整成本条款的权重。此外，使用优化的参考将立足点纠正，以将机器人推向目标。我们在与Aliengo机器人的不同情况下在模拟和实验中展示了方法的有效性。
Model Predictive Control (MPC) approaches are widely used in robotics, since they guarantee feasibility and allow the computation of updated trajectories while the robot is moving. They generally require heuristic references for the tracking terms and proper tuning of the parameters of the cost function in order to obtain good performance. For instance, when a legged robot has to react to disturbances from the environment (e.g., recover after a push) or track a specific goal with statically unstable gaits, the effectiveness of the algorithm can degrade. In this work, we propose a novel optimization-based Reference Generator which exploits a Linear Inverted Pendulum (LIP) model to compute reference trajectories for the Center of Mass while taking into account the possible under-actuation of a gait (e.g., in a trot). The obtained trajectories are used as references for the cost function of the Nonlinear MPC presented in our previous work. We also present a formulation that ensures guarantees on the response time to reach a goal without the need to tune the weights of the cost terms. In addition, footholds are corrected using the optimized reference to drive the robot towards the goal. We demonstrate the effectiveness of our approach both in simulations and experiments in different scenarios with the Aliengo robot.
