Learning and Chaining of Motor Primitives for Goal-Directed Locomotion of a Snake-Like Robot with Screw-Drive Units
Learning and Chaining of Motor Primitives for Goal-Directed Locomotion of a Snake-Like Robot with Screw-Drive Units
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DOI：
10.5772/61621
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发表时间：
2015-12
影响因子：
2.3
通讯作者：
Sromona Chatterjee;Timo Nachstedt;M. Tamosiunaite;F. Wörgötter;Y. Enomoto;Ryo Ariizumi;F. Matsuno;P. Manoonpong
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作者：
Sromona Chatterjee;Timo Nachstedt;M. Tamosiunaite;F. Wörgötter;Y. Enomoto;Ryo Ariizumi;F. Matsuno;P. Manoonpong
运动原语为脊椎动物和无脊椎动物的复杂行为提供了一个模块化的组织。受此启发，我们为带有螺旋驱动单元的复杂蛇形机器人生成了运动原语，然后将它们串联并组合起来，从而为机器人提供了一个多功能的、目标导向的运动。机器人的行为原语是使用一种称为“路径积分策略改进”（PI2）的强化学习方法生成的。PI2在数值上很简单，并且能够处理高维系统。在这里，PI2通过寻找合适的运动控制参数，如关节角度和螺杆驱动单元速度，以协调的方式学习机器人的电机控制。因此，它能够生成大量的运动原语，这些原语被选择性地存储以形成一个原语库。在仿真机器人上进行了学习过程，并成功地将学习到的参数传递到真实机器人上。B…
Motor primitives provide a modular organization to complex behaviours in both vertebrates and invertebrates. Inspired by this, here we generate motor primitives for a complex snake-like robot with screw-drive units, and thence chain and combine them, in order to provide a versatile, goal-directed locomotion for the robot. The behavioural primitives of the robot are generated using a reinforcement learning approach called “Policy Improvement with Path Integrals” (PI2). PI2 is numerically simple and has the ability to deal with high-dimensional systems. Here, PI2 is used to learn the robot's motor controls by finding proper locomotion control parameters, like joint angles and screw-drive unit velocities, in a coordinated manner for different goals. Thus, it is able to generate a large repertoire of motor primitives, which are selectively stored to form a primitive library. The learning process was performed using a simulated robot and the learned parameters were successfully transferred to the real robot. B...