论文标题
通过轨迹优化和模型预测控制，连续跳跃在步进石上的腿机器人
Continuous Jumping for Legged Robots on Stepping Stones via Trajectory Optimization and Model Predictive Control
论文作者
论文摘要
在腿部机器人的机车上，执行高度敏捷的动态动作，例如跳跃或在不均匀的踏脚石上奔跑一直是一个具有挑战性的问题。本文提出了一个结合轨迹优化和模型预测控制的框架，以在踏脚石上执行强大的连续跳跃。在我们的方法中，我们首先利用基于机器人的全非线性动力学的轨迹优化来生成各种跳跃距离的周期性跳跃轨迹。然后，基于模型预测控制的跳跃控制器设计用于实现平滑的跳跃过渡，从而使机器人能够在步进石上实现连续跳跃。得益于将MPC作为实时反馈控制器的合并，该提议的框架也得到了验证，可以对机器人动力学上的高度扰动和模型不确定性具有不均匀的平台。
Performing highly agile dynamic motions, such as jumping or running on uneven stepping stones has remained a challenging problem in legged robot locomotion. This paper presents a framework that combines trajectory optimization and model predictive control to perform robust and consecutive jumping on stepping stones. In our approach, we first utilize trajectory optimization based on full-nonlinear dynamics of the robot to generate periodic jumping trajectories for various jumping distances. A jumping controller based on a model predictive control is then designed for realizing smooth jumping transitions, enabling the robot to achieve continuous jumps on stepping stones. Thanks to the incorporation of MPC as a real-time feedback controller, the proposed framework is also validated to be robust to uneven platforms with unknown height perturbations and model uncertainty on the robot dynamics.
