Stable walking on variable visco-elastic terrains using meta-parameters for passive state migration
Stable walking on variable visco-elastic terrains using meta-parameters for passive state migration
复制标题
使用元参数进行被动状态迁移，在可变粘弹性地形上稳定行走
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
D. Nanayakkara
中科院分区：
文献类型：
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作者：
Valerio Pereno;Kya Shoar;G. Bartoli;F. Bianchi;D. Nanayakkara
本文研究了如何步行者可以估计一组任意的状态变量的变化时，迁移粘弹性的理由。状态变量是行走体的粘弹性设置和软地形参数两者的函数。一个无轮缘车轮模型，开发使用拉格朗日方法，以获得分析解决方案，迁移跨地面条件。然后制定了一种算法，以确定作为迁移所涉地面参数和枢纽参数之差的函数的变量的稳定值。然后使用多项式近似法外推该差异的广义迁移元参数Δg。Δg可用于估计给定实际和先前地面参数信息的状态下的预期变化。第二个参数Δh描述了给定地形上给定状态的局部变化，用于生成预测算法，该算法能够在地面参数发生突变时稳定无轮辋车轮设置。我们用恒定的扭矩驱动无框轮，使其针对给定的地面粘弹性阻抗分布和其自身的垂直粘弹性阻抗来开发任何速度曲线。根据两个迁移元参数（Δg和Δr）改变地面，确保局部和迁移稳定性。
This paper investigates how a walker could estimate the variability of an arbitrary set of state variables when migrating on visco-elastic grounds. The state variables are a function of both the visco-elastic settings of the walking body and soft terrain parameters. A rimless wheel model was developed using a Lagrangian approach in order to obtain analytical solutions for migration across ground conditions. An algorithm was then developed to determine the steady value of the variables as a function of the difference in ground and hub parameters involved in the migration. A generalised migration metaparameter, Δg, function of this difference, was then extrapolated using polynomial approximation. Δg can be used to estimate the expected variability at a state given information on actual and previous ground parameters. A second parameter, Δh, describing local variability of a given state on a given terrain, is used to generate a predictive algorithm capable of stabilising the rimless wheel setup when subject to an abrupt change in ground parameters. We actuate the rimless wheel with a constant torque leaving it to develop any speed profile for a given visco-elastic impedance distribution of the ground and its own vertical visco-elastic impedance. The ground is altered depending on the two migration meta-parameters (Δg and Δr), ensuring both local and migration stability.