This work presents a two part framework for online planning and execution of dynamic aerial motions on a quadruped robot. Motions are planned via a centroidal momentum-based nonlinear optimization that is general enough to produce rich sets of novel dynamic motions based solely on the user-specified contact schedule and desired launch velocity of the robot. Since this nonlinear optimization is not tractable for real-time receding horizon control, motions are planned once via nonlinear optimization in preparation of an aerial motion and then tracked continuously using a variational-based optimal controller that offers robustness to the uncertainties that exist in the real hardware such as modeling error or disturbances. Motion planning typically takes between 0.05-0.15 seconds, while the optimal controller finds stabilizing feedback inputs at 500 Hz. Experimental results on the MIT Mini Cheetah demonstrate that the framework can reliably produce successful aerial motions such as jumps onto and off of platforms, spins, flips, barrel rolls, and running jumps over obstacles.
翻译:这项工作为对四重机器人进行在线规划和实施动态空中运动提供了两个部分框架。 动议是通过一个基于近机器人动力的非线性优化规划的,该优化一般地足以产生大量新的动态动议, 仅以用户指定的接触时间表和机器人预期的发射速度为基础。 由于这种非线性优化无法实时进行实时后退地平线控制, 因此通过非线性优化来准备空中运动, 然后利用一个基于变异的最佳控制器来连续跟踪这些动议, 该控制器为模拟错误或扰动等真实硬件中存在的不确定性提供了稳健性。 运动规划通常在0.05-0.15秒之间进行, 而最佳控制器则在500赫兹找到稳定的反馈输入。 麻省理工学院小型Cheetah的实验结果表明, 框架可以可靠地产生成功的空中运动, 如跳上和跳出平台、 旋转、 翻转、 桶滚转和跳过障碍。