Quadratic encoding of optimized humanoid walking
Quadratic encoding of optimized humanoid walking
复制标题
优化人形行走的二次编码
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
C. Atkeson
中科院分区：
文献类型：
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作者：
Junggon Kim;N. Pollard;C. Atkeson
在本文中，我们表明，最佳的步进轨迹和轨迹成本的步行机器人在粗糙的地形可以编码为简单的二次函数的初始状态和脚步序列。为了找到这种编码，我们通过对输入空间（初始状态和脚步序列）进行采样并为每个样本求解基于物理的轨迹优化问题，为3D人形模型构建了一个最佳步行轨迹数据库。然后，通过使用最小二乘法拟合数据来获得函数系数。所提出的方法的性能进行评估，通过比较的功能值与其他最佳的步行运动数据产生不同的脚步样本。作为应用，我们使用二次函数来计算在使用A* 算法寻找最佳脚步序列时所使用的努力成本。我们的研究表明，一个简单的函数可以有效地编码最佳步行，这提供了一个快速的替代在线优化步行与全身动力学。
In this paper we show that optimal stepping trajectories and trajectory cost for a walking biped robot on rough terrain can be encoded as simple quadratic functions of initial state and footstep sequence. In order to find this encoding, we build a database of optimal walking trajectories for a 3D humanoid model by sampling the input space (initial state and footstep sequence) and solving a physically-based trajectory optimization problem for each sample. Then, the function coefficients are obtained by fitting the data using least squares. The performance of the proposed method is evaluated by comparing the function values with other optimal walking motion data generated with different footstep samples. As an application, we use a quadratic function to calculate the effort cost used in finding an optimal footstep sequence with an A* algorithm. Our study shows that a simple function can encode optimal walking effectively, which provides a fast alternative to online optimization of walking with full body dynamics.