Minimax differential dynamic programming: application to a biped walking robot
Minimax differential dynamic programming: application to a biped walking robot
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DOI：
10.1109/iros.2003.1248926
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发表时间：
2003-12
期刊：
影响因子：
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通讯作者：
J. Morimoto;G. Zeglin;C. Atkeson
中科院分区：
文献类型：
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作者：
J. Morimoto;G. Zeglin;C. Atkeson
在高维状态空间中，利用微分动态规划和极大极小准则，提出了一种鲁棒控制策略设计方法。作为一个例子，我们将我们的方法应用到一个模拟的五连杆机器人。结果表明，较低的联合扭矩从最优控制策略相比，手动调整PD伺服控制器。结果还表明，模拟的机器人可以成功地步行与未知的干扰，导致控制器产生的标准微分动态规划和手动调谐PD伺服失败。学习补偿建模误差和以前未知的干扰结合鲁棒控制设计也证明了。我们还将所提出的方法应用于真实的机器人摆动腿轨迹的优化。
We developed a robust control policy design method in high-dimensional state space by using differential dynamic programming with a minimax criterion. As an example, we applied our method to a simulated five link biped robot. The results show lower joint torques from the optimal control policy compared to a hand-tuned PD servo controller. Results also show that the simulated biped robot can successfully walk with unknown disturbances that cause controllers generated by standard differential dynamic programming and the hand-tuned PD servo to fail. Learning to compensate for modeling error and previously unknown disturbances in conjunction with robust control design is also demonstrated. We also applied proposed method to a real biped robot for optimizing swing leg trajectories.