Stefanovic Filip, Galiana Henrietta L
Department of Biomedical Engineering, McGill University, 3775, rue University, Room 316, Montréal, QC H3A 2B4, Canada.
Biomed Eng Online. 2014 Nov 20;13:151. doi: 10.1186/1475-925X-13-151.
Spinal-like regulators have recently been shown to support complex behavioral patterns during volitional goal-oriented reaching paradigms. We use an interpretation of the adaptive spinal-like controller as inspiration for the development of a controller for a robotic limb. It will be demonstrated that a simulated robot arm with linear actuators can achieve biological-like limb movements. In addition, it will be shown that programmability in the regulator enables independent spatial and temporal changes to be defined for movement tasks, downstream of central commands using sensory stimuli. The adaptive spinal-like controller is the first to demonstrate such behavior for complex motor behaviors in multi-joint limb movements.
The controller is evaluated using a simulated robotic apparatus and three goal-oriented reaching paradigms: 1) shaping of trajectory profiles during reaching; 2) sensitivity of trajectories to sudden perturbations; 3) reaching to a moving target. The experiments were designed to highlight complex motor tasks that are omitted in earlier studies, and important for the development of improved artificial limb control.
In all three cases the controller was able to reach the targets without a priori planning of end-point or segmental motor trajectories. Instead, trajectory spatio-temporal dynamics evolve from properties of the controller architecture using the spatial error (vector distance to goal). Results show that curvature amplitude in hand trajectory paths are reduced by as much as 98% using simple gain scaling techniques, while adaptive network behavior allows the regulator to successfully adapt to perturbations and track a moving target. An important observation for this study is that all motions resemble human-like movements with non-linear muscles and complex joint mechanics.
The controller shows that it can adapt to various behavioral contexts which are not included in previous biomimetic studies. The research supplements an earlier study by examining the tunability of the spinal-like controller for complex reaching tasks. This work is a step toward building more robust controllers for powered artificial limbs.
最近研究表明，类似脊髓的调节器在自主目标导向的伸手范式中支持复杂的行为模式。我们将适应性类似脊髓的控制器的一种解释作为开发机器人肢体控制器的灵感来源。将证明，具有线性致动器的模拟机器人手臂可以实现类似生物的肢体运动。此外，还将表明，调节器中的可编程性能够在使用感官刺激的中央命令下游，为运动任务定义独立的空间和时间变化。适应性类似脊髓的控制器首次展示了在多关节肢体运动的复杂运动行为中的这种行为。
使用模拟机器人装置和三种目标导向的伸手范式对控制器进行评估：1）伸手过程中轨迹轮廓的塑造；2）轨迹对突然扰动的敏感性；3）伸向移动目标。这些实验旨在突出早期研究中省略的复杂运动任务，这些任务对于改进人工肢体控制的发展很重要。
在所有三种情况下，控制器都能够在没有预先规划端点或节段性运动轨迹的情况下到达目标。相反，轨迹的时空动态从控制器架构的属性使用空间误差（到目标的矢量距离）演变而来。结果表明，使用简单的增益缩放技术，手部轨迹路径中的曲率幅度可降低多达98%，而自适应网络行为使调节器能够成功适应扰动并跟踪移动目标。本研究的一个重要观察结果是，所有运动都类似于具有非线性肌肉和复杂关节力学的人类运动。
该控制器表明它可以适应先前仿生研究中未包括的各种行为背景。该研究通过检查类似脊髓的控制器对复杂伸手任务的可调性，补充了早期的一项研究。这项工作是朝着为动力人工肢体构建更强大的控制器迈出的一步。
