As the number of the robot's degrees of freedom increases, the implementation of robot motion becomes more complex and difficult. In this study, we focus on learning 6DOF-grasping motion and consider dividing the grasping motion into multiple tasks. We propose to combine imitation and reinforcement learning in order to facilitate a more efficient learning of the desired motion. In order to collect demonstration data as teacher data for the imitation learning, we created a virtual reality (VR) interface that allows humans to operate the robot intuitively. Moreover, by dividing the motion into simpler tasks, we simplify the design of reward functions for reinforcement learning and show in our experiments a reduction in the steps required to learn the grasping motion.
翻译:随着机器人自由度的增加,机器人运动的实施变得更加复杂和困难。在本研究中,我们侧重于学习6DOF的雕刻运动,并考虑将抓捕运动分为多项任务。我们提议将模仿和强化学习结合起来,以便更有效地学习所需的运动。为了收集示范数据,作为模拟学习的教师数据,我们创建了一个虚拟现实界面,使人类能够直觉操作机器人。此外,通过将动作分为更简单的任务,我们简化了用于强化学习的奖励功能的设计,并在我们的实验中显示学习捕捉运动所需步骤的减少。