In this paper, a kinematically modular approach to robot control is presented. The method involves structures called Elementary Dynamic Actions and a network model combining these elements. With this control framework, a rich repertoire of movements can be generated by combination of basic kinematic modules. Each module can be learned by Imitation Learning, thereby resulting in a modular learning strategy for robot control. The theoretical foundations and their real robot implementation are presented. Using a KUKA LBR iiwa14 robot, three tasks were considered: (1) generating a sequence of discrete movements, (2) generating a combination of discrete and rhythmic movements, and (3) a drawing and erasing task. The obtained results indicate that this modular approach has the potential to simplify the generation of a diverse range of robot actions.

翻译：本文提出了一种运动模块化机器人控制方法，该方法涉及称为“基本动态动作”的结构以及结合这些元素的网络模型。通过该控制框架，可组合基本运动模块生成丰富的动作集。每个模块可通过模仿学习获得，从而形成一种模块化的机器人控制学习策略。本文阐述了理论基础及其在真实机器人上的实现。使用KUKA LBR iiwa14机器人，考虑了三个任务：（1）生成离散运动序列，（2）生成离散与节律运动的组合，（3）绘制与擦除任务。结果表明，这种模块化方法有望简化多种机器人动作的生成。