Iterative Learning without Reinforcement or Reward for Multijoint Movements: A Revisit of Bernstein's DOF Problem on Dexterity
Iterative Learning without Reinforcement or Reward for Multijoint Movements: A Revisit of Bernstein's DOF Problem on Dexterity
复制标题
多关节运动无强化或奖励的迭代学习：重温伯恩斯坦关于敏捷性的自由度问题
DOI：
10.1155/2010/217867
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
K. Tahara
中科院分区：
文献类型：
--
作者：
S. Arimoto;M. Sekimoto;K. Tahara
一个被设计成模仿人类的机器人在运动学上变得多余，它的总自由度变得大于描述给定任务所需的物理变量的数量。运动冗余有助于提高灵活性和多功能性，但它会引起逆运动学的不适定性问题，从任务
空间到关节空间。这种不适定性最初是由伯恩斯坦发现的，他试图揭开
中枢神经系统，以及它如何很好地协调一个骨骼运动系统与许多自由度以复杂的方式相互作用。在
在机器人研究的历史上，这种不适定性还没有被直接解决，而是通过引入
人工性能指标，并通过最小化唯一地确定逆运动学解。本文探讨
这种伯恩斯坦的问题，并提出了一种新的方法，解决了自然的方式，而无需调用
任何人工索引。首先，给定一条冗余度机器人手臂在水平面上的曲线，其端点被强制跟踪
曲线，存在唯一的理想关节轨迹的证明。第二，这种唯一确定的运动可以是
通过迭代学习最终获得作为联合控制信号，而无需强化或奖励。
A robot designed to mimic a human becomes kinematically redundant and its total degrees of freedom becomes larger than the number of physical variables required for describing a given task. Kinematic redundancy may contribute to enhancement of dexterity and versatility but it incurs a problem of ill-posedness of inverse kinematics from the task
space to the joint space. This ill-posedness was originally found by Bernstein, who tried to unveil the secret of the
central nervous system and how nicely it coordinates a skeletomotor system with many DOFs interacting in complex ways. In
the history of robotics research, such ill-posedness has not yet been resolved directly but circumvented by introducing
an artificial performance index and determining uniquely an inverse kinematics solution by minimization. This paper tackles
such Bernstein's problem and proposes a new method for resolving the ill-posedness in a natural way without invoking
any artificial index. First, given a curve on a horizontal plane for a redundant robot arm whose endpoint is imposed to trace
the curve, the existence of a unique ideal joint trajectory is proved. Second, such a uniquely determined motion can be
acquired eventually as a joint control signal through iterative learning without reinforcement or reward.
影响因子：
9.2
作者：
YOSHIKAWA, T
通讯作者：
YOSHIKAWA, T