In legged locomotion, the relationship between different gait behaviors and energy consumption must consider the full-body dynamics and the robot control as a whole, which cannot be captured by simple models. This work studies the robot dynamics and whole-body optimal control as a coupled system to investigate energy consumption during balance recovery. We developed a 2-phase nonlinear optimization pipeline for dynamic stepping, which generates reachability maps showing complex energy-stepping relations. We optimize gait parameters to search all reachable locations and quantify the energy cost during dynamic transitions, which allows studying the relationship between energy consumption and stepping locations given different initial conditions. We found that to achieve efficient actuation, the stepping location and timing can have simple approximations close to the underlying optimality. Despite the complexity of this nonlinear process, we show that near-minimal effort stepping locations fall within a region of attractions, rather than a narrow solution space suggested by a simple model. This provides new insights into the non-uniqueness of near-optimal solutions in robot motion planning and control, and the diversity of stepping behavior in humans.

中文翻译：

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人形机器人的各种平衡策略和高能效步进的可到达性图

在腿式运动中，不同步态行为与能量消耗之间的关系必须考虑全身动力学和整个机器人的控制，而这不能用简单的模型来捕获。这项工作将机器人动力学和整体最优控制作为一个耦合系统进行研究，以研究平衡恢复过程中的能耗。我们开发了用于动态步进的两阶段非线性优化管线，该管线生成了显示复杂能量-步进关系的可达性图。我们优化步态参数以搜索所有可到达的位置并量化动态过渡期间的能源成本，这允许研究在给定不同初始条件的情况下能量消耗与步进位置之间的关系。我们发现，要实现高效的驱动，步进位置和时序可以具有接近基础最优性的简单近似值。尽管此非线性过程很复杂，但我们表明，接近最小的作用力步进位置落在引力区域内，而不是简单模型建议的狭窄解空间。这为机器人运动计划和控制中非最优解决方案的非唯一性以及人类踩踏行为的多样性提供了新的见解。