Towards biomimetic control of robotic or paralyzed limbs

我们的长期目标是从生物运动中学习，并为人工系统（机器人，假肢）和辅助人类控制（FES，神经接口）设计有效和新颖的控制策略。迄今为止，我们专注于并行子目标的两个流：* 1-适用于非线性参数场，切换混合策略和强加拓扑的困难背景下的生物运动系统的新分析工具。过去由NSERC资助，我们生产了软件创新，现在由NSERC/ I2I支持：在切换系统中创建响应模式的自动分类和识别工具，以估计每种模式的动态，尽管切换特性。它们的目标是分发给该领域的神经科学家、神经耳科医生和临床医生。* 2-基于脑干和脊髓神经回路的特殊性质（拓扑结构）的眼-头和眼反射生物控制策略新模型（CIHR资助）。这些模型在行为和神经层面上改变了对数据的解释，并提出了在更自然的混合感觉环境（如日常生活）中测试运动系统完整性的新方案。现在这才成为可能，因为我们的算法可以处理各种情况。最近，对手臂伸展的探索（由NSERC资助）预测，我们在眼-头协调中使用的控制策略与灵长类动物手臂或腿的轨迹和脊髓的拓扑结构一致。其结果是比机器人文献中通常使用的控制简单得多-即没有计划的运动。*所有这些系统在空间组织和感觉运动融合方面都使用类似的网络拓扑结构。这暗示了一种可能适用于所有平台的通用控制理论，无论它们是堆叠的、旋转的还是分段的肢体。因此，长期目标是：*为移动系统形式化一种仿生控制策略，使其无需先验轨迹规划即可执行简单任务

Our long-term objectives are to learn from biological movement and devise efficient and novel control strategies for artificial systems (robots, prostheses) and for assisted human control (FES, neural interfaces). To date, we have focused on two streams in parallel sub-objectives:* 1- New analytical tools applicable to biological movement systems in the difficult context of non-linear parametric fields, switched hybrid strategies and imposed topologies. Funded by NSERC in the past, we produced software innovations now supported by NSERC/ I2I: to create automated classification of response modes in switched systems and identification tools to estimate the dynamics of each mode despite switching characteristics. They are targeted for distribution to Neuroscientists, Neuro-otologists and Clinicians in the field.* 2- Novel models of biological control strategies for eye-head and ocular reflexes (funded by CIHR) based on the special nature (topology) of neural circuits in the brainstem and spinal cord. These models change the interpretation of data at both behavioural and neural levels, and suggest new protocols to test the integrity of motor systems in more natural mixed-sensory environments, as in daily life. This is only possible now because our algorithms can handle diverse conditions. More recently, explorations on arm reaching (funded by NSERC) predict that our control strategies used in eye-head coordination are consistent with primate arm or leg trajectories and the topology of the spinal cord. The result is much simpler control than typically used in the robotic literature - i.e. movement without planning. * All of these systems use network topologies similar in their spatial organization and in the use of sensorimotor fusion. This suggests a possible general control theory for all platforms, be they stacked and rotatory, or segmental limbs. So the long-term goal is: * TO FORMALIZE A BIOMIMETIC CONTROL STRATEGY FOR MOVING SYSTEMS THAT WILL ALLOW EXECUTION OF SIMPLE TASKS WITHOUT A-PRIORI TRAJECTORY PLANNIN