Bipedal walking on rough terrain using manifold control
Bipedal walking on rough terrain using manifold control
复制标题
使用流形控制在崎岖地形上双足行走
DOI：
10.1109/iros.2007.4399588
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
W. Smart
中科院分区：
文献类型：
--
作者：
Tom Erez;W. Smart
本文提出了一种使周期性行为适应任务参数逐渐变化的算法。由于学习高维域中的最优控制会受到“维数灾难”的影响，因此我们仅沿着步态遍历的极限环对策略进行参数化，从而将计算工作集中在嵌入高维状态空间的封闭一维流形上。我们以初始步态为出发点，并在稍微修改任务和使步态适应此修改之间进行迭代。这会创建一系列步态，每个步态都针对任务的不同变体进行了优化。由于该序列中的每两个步态非常相似，因此整个序列跨越二维流形，并且组合该二维流形中的所有策略为系统提供了额外的鲁棒性。我们在双足机器人的两个模拟上展示了我们的方法 - 罗盘步态步行者（四维系统）和兔子（十维系统）。步行者的步态适应地面坡度的一系列变化，当序列中的所有策略结合起来时，步行者可以安全地穿越每一步坡度都会变化的崎岖地形。
This paper presents an algorithm for adapting periodic behavior to gradual shifts in task parameters. Since learning optimal control in high dimensional domains is subject to the 'curse of dimensionality', we parametrize the policy only along the limit cycle traversed by the gait, and thus focus the computational effort on a closed one-dimensional manifold, embedded in the high-dimensional state space. We take an initial gait as a departure point, and iterate between modifying the task slightly, and adapting the gait to this modification. This creates a sequence of gaits, each optimized for a different variant of the task. Since every two gaits in this sequence are very similar, the whole sequence spans a two-dimensional manifold, and combining all policies in this 2-manifold provides additional robustness to the system. We demonstrate our approach on two simulations of bipedal robots - the compass gait walker, which is a four-dimensional system, and RABBIT, which is ten-dimensional. The walkers' gaits are adapted to a sequence of changes in the ground slope, and when all policies in the sequence are combined, the walkers can safely traverse a rough terrain, where the incline changes at every step.