Functional autonomous systems often realize complex tasks by utilizing state machines comprised of discrete primitive behaviors and transitions between these behaviors. This architecture has been widely studied in the context of quasi-static and dynamics-independent systems. However, applications of this concept to dynamical systems are relatively sparse, despite extensive research on individual dynamic primitive behaviors, which we refer to as "motion primitives." This paper formalizes a process to determine dynamic-state aware conditions for transitions between motion primitives in the context of safety. The result is framed as a "motion primitive graph" that can be traversed by standard graph search and planning algorithms to realize functional autonomy. To demonstrate this framework, dynamic motion primitives -- including standing up, walking, and jumping -- and the transitions between these behaviors are experimentally realized on a quadrupedal robot.
翻译：功能自治系统通常通过使用由离散原始行为和这些行为之间的转变组成的国家机器来完成复杂的任务。 这一结构已经在准静态和动态独立系统的背景下进行了广泛研究。 但是,尽管对个体动态原始行为进行了广泛的研究,我们称之为“感动原始人 ”, 但是,这个概念对动态系统的应用相对较少。 本文正式确定了一个进程, 以确定动态状态意识条件, 以便在安全背景下从运动原始人之间转型。 结果被设计成“ 感动原始图 ”, 可以通过标准图表搜索和规划算法进行穿透, 以便实现功能自主。 为了展示这个框架, 动态原始人 — 包括站起来、 步行和跳跃 — 动态原始人, 以及这些行为之间的转变是实验性地在四重机器人上实现的。
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