We present a technique for automatically synthesizing walking and running controllers for physically-simulated 3D humanoid characters. The sagittal hip, knee, and ankle degrees-of-freedom are actuated using a set of eight Hill-type musculotendon models in each leg, with biologically-motivated control laws. The parameters of these control laws are set by an optimization procedure that satisfies a number of locomotion task terms while minimizing a biological model of metabolic energy expenditure. We show that the use of biologically-based actuators and objectives measurably increases the realism of gaits generated by locomotion controllers that operate without the use of motion capture data, and that metabolic energy expenditure provides a simple and unifying measurement of effort that can be used for both walking and running control optimization.

中文翻译：

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使用基于生物的执行器和目标优化运动控制器

我们提出了一种自动合成步行和跑步控制器的技术，用于物理模拟的 3D 人形角色。矢状髋关节、膝关节和踝关节的自由度由每条腿的一组 8 个希尔型肌腱模型驱动，具有生物驱动的控制规律。这些控制法则的参数由满足许多运动任务项同时最小化代谢能量消耗的生物模型的优化程序设置。我们表明，使用基于生物的执行器和目标可显着增加由不使用运动捕捉数据运行的运动控制器生成的步态的真实性，并且代谢能量消耗提供了一种简单而统一的努力测量，可用于步行和跑步控制优化。