论文标题
倾斜地形上强大的四足运动：一种线性政策方法
Robust Quadrupedal Locomotion on Sloped Terrains: A Linear Policy Approach
论文作者
论文摘要
在本文中，为了在低成本硬件中快速部署运动步态，我们使用线性策略来实现四倍的机器人中的末端轨迹，stoch $ 2 $。特别是，末端轨迹的参数是通过线性反馈策略来形成的，该策略将躯干方向和地形斜率作为输入。相应所需的关节角是通过逆运动学求解器获得的，并通过PID控制定律进行跟踪。增强随机搜索，无模型和无梯度学习算法用于训练该线性策略。仿真结果表明，所产生的步行对地形斜率变化和外部推动是可靠的。该方法不仅在计算上是轻量重量，而且还使用机器人中的最小感应和致动功能，从而证明了方法是合理的。
In this paper, with a view toward fast deployment of locomotion gaits in low-cost hardware, we use a linear policy for realizing end-foot trajectories in the quadruped robot, Stoch $2$. In particular, the parameters of the end-foot trajectories are shaped via a linear feedback policy that takes the torso orientation and the terrain slope as inputs. The corresponding desired joint angles are obtained via an inverse kinematics solver and tracked via a PID control law. Augmented Random Search, a model-free and a gradient-free learning algorithm is used to train this linear policy. Simulation results show that the resulting walking is robust to terrain slope variations and external pushes. This methodology is not only computationally light-weight but also uses minimal sensing and actuation capabilities in the robot, thereby justifying the approach.
