Towards biomimetic control of robotic or paralyzed limbs

我们的长期目标是从生物运动中学习，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。到目前为止，我们侧重于并行的子目标中的两个流：*1-适用于在非线性参数场、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。过去在NSERC的资助下，我们产生了现在得到NSERC/I2I支持的软件创新：创建交换系统中响应模式的自动分类和识别工具，以评估每种模式的动态，而不考虑交换特性。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)，针对眼头和眼反射的生物控制策略的新模型(由CIHR资助)。这些模型改变了对行为和神经层面数据的解释，并提出了新的方案，以测试在更自然的混合感觉环境中运动系统的完整性，如在日常生活中。这现在才有可能，因为我们的算法可以处理不同的情况。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手臂或腿的轨迹以及脊髓的拓扑结构一致。其结果是控制比通常在机器人文献中使用的要简单得多--即无需规划的移动。*所有这些系统都使用在其空间组织和传感器运动融合使用方面相似的网络拓扑。这提出了一种可能的通用控制理论，适用于所有平台，无论是堆叠和旋转的平台，还是节段式肢体。因此，我们的长期目标是：*制定一种用于移动系统的仿生控制策略，它将允许执行简单的任务，而无需事先规划轨迹

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