Analytical Center of Mass Trajectory Generation for Humanoid Walking and Running with Continuous Gait Transitions

Tobias Egle, Johannes Englsberger, C. Ott
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引用次数: 2

Abstract

We present an analytical trajectory generation framework for the combined computation of multiple walking and running sequences with continuous gait transitions. This framework builds on the Divergent Component of Motion (DCM)-based walking algorithm and the spline-based trajec-tory generation of the Biologically Inspired Deadbeat (BID) control for running. We describe our approach to generating closed-form center of mass (CoM) trajectories for walking and running by alternately linking the two gaits through continuity constraints. Thereby, we distinguish between vertical and horizontal planning. The vertical trajectory is computed in a forward recursion from the first to the last gait sequence. Due to the coupling of the gait sequences in the horizontal direction, we show the efficient generation of the horizontal CoM trajectory in a single matrix calculation. Subsequently, we unify the control strategies using a DCM tracking controller for the complete trajectory and integrate the proposed framework into an inverse dynamics-based whole-body controller. Finally, the presented approaches are validated in simulations with the humanoid robot Toro.
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连续步态变换的仿人行走和奔跑质量轨迹生成分析中心
提出了一种分析轨迹生成框架,用于连续步态转换的多步跑序列的联合计算。该框架建立在基于运动发散分量(DCM)的行走算法和基于样条的生物启发无差拍(BID)控制的轨迹生成的基础上。我们描述了通过连续性约束交替连接行走和跑步两种步态来生成封闭形式质心(CoM)轨迹的方法。因此,我们区分垂直规划和水平规划。垂直轨迹从第一个到最后一个步态序列以正向递归的方式计算。由于步态序列在水平方向上的耦合,我们展示了在单矩阵计算中有效地生成水平CoM轨迹。随后,我们使用DCM跟踪控制器统一控制策略,并将所提出的框架集成到基于逆动力学的全身控制器中。最后,用仿人机器人Toro进行了仿真验证。
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