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Learning to push and learning to move: the adaptive control of contact forces

机译:学习推动和学习移动:接触力的自适应控制

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摘要

To be successful at manipulating objects one needs to apply simultaneously well controlled movements and contact forces. We present a computational theory of how the brain may successfully generate a vast spectrum of interactive behaviors by combining two independent processes. One process is competent to control movements in free space and the other is competent to control contact forces against rigid constraints. Free space and rigid constraints are singularities at the boundaries of a continuum of mechanical impedance. Within this continuum, forces and motions occur in “compatible pairs” connected by the equations of Newtonian dynamics. The force applied to an object determines its motion. Conversely, inverse dynamics determine a unique force trajectory from a movement trajectory. In this perspective, we describe motor learning as a process leading to the discovery of compatible force/motion pairs. The learned compatible pairs constitute a local representation of the environment's mechanics. Experiments on force field adaptation have already provided us with evidence that the brain is able to predict and compensate the forces encountered when one is attempting to generate a motion. Here, we tested the theory in the dual case, i.e., when one attempts at applying a desired contact force against a simulated rigid surface. If the surface becomes unexpectedly compliant, the contact point moves as a function of the applied force and this causes the applied force to deviate from its desired value. We found that, through repeated attempts at generating the desired contact force, subjects discovered the unique compatible hand motion. When, after learning, the rigid contact was unexpectedly restored, subjects displayed after effects of learning, consistent with the concurrent operation of a motion control system and a force control system. Together, theory and experiment support a new and broader view of modularity in the coordinated control of forces and motions.
机译:为了成功地操纵物体,需要同时施加良好控制的运动和接触力。我们提出一种计算理论,说明大脑如何通过结合两个独立的过程来成功地产生广泛的交互行为。一个过程能够控制自由空间中的运动,而另一个过程则能够克服刚性约束来控制接触力。自由空间和刚性约束是连续的机械阻抗边界上的奇点。在这个连续体中,力和运动在通过牛顿动力学方程连接的“兼容对”中发生。施加到对象上的力决定了它的运动。相反,逆动力学从运动轨迹确定唯一的力轨迹。从这个角度来看,我们将运动学习描述为导致发现兼容的力/运动对的过程。学到的兼容对构成了环境力学的局部表示。力场适应性实验已经为我们提供了证据,证明大脑能够预测和补偿当人们尝试产生运动时遇到的力。在这里,我们在双重情况下测试了该理论,即当人们试图对模拟的刚性表面施加所需的接触力时。如果表面出乎意料地变柔顺,则接触点将根据施加的力而移动,这将导致施加的力偏离其期望值。我们发现,通过反复尝试产生所需的接触力,受试者发现了独特的兼容手部动作。在学习后,如果刚度恢复了刚性接触,则受过学习的影响后显示的对象与运动控制系统和力控制系统的同时操作一致。理论和实验共同支持对力和运动进行协调控制的模块化的新视野。

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