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Acquiring of walking behavior for four-legged robots using actor-critic method based on policy gradient

机译:基于政策梯度的演员 - 批评方法获取四足球机的行走行为

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Actor-critic method based on policy gradient is an effective method for problems with high-dimensional learning space. In walking behavior of robots, the movement of robot's joint is cyclic. For this purpose, we apply closed-loops of B-spline curve to cyclic movement. Hence, we propose a method combined actor-critic method based on policy gradient with B-spline curve. In this method, B-spline curve uses for controlling target such as joints in robot on continuous space. By using B-spline curve, the target for control can move smoothly and flexible. In this paper, we applied this method to a four-legged robot with 12 joints and simulated on the Open Dynamics Engine (ODE) which is a dynamics simulation software. The simulation results show that robots succeeded in getting walking behavior.
机译:基于政策梯度的演员 - 批评方法是高维学习空间问题的有效方法。在机器人的行走行为中,机器人关节的运动是循环的。为此目的,我们将B样条曲线的闭环应用于循环运动。因此,我们提出了一种基于B样条曲线的政策梯度组合的方法组合的演员 - 批评方法。在该方法中,B样条曲线用于控制连续空间上的机器人中的目标等目标。通过使用B样条曲线,控制目标可以平稳且柔韧。在本文中,我们将这种方法应用于具有12个关节的四腿机器人,并在开放动态发动机(ode)上模拟,这是动态仿真软件。仿真结果表明,机器人成功地获得了行走行为。

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