Sensory-Motor Coordination based Movement Learning and Dynamic Adaptation in Human Friendly Robot

在第三年，我们改进了已经在第二年完成的基于神经元的运动产生器的适应性，以适应更广泛的应用领域，特别是在与人类运动行为的交互方面。然而，人体与肢体辅助装置之间的同步缺乏同步和主动控制机制。因此，需要一种能够产生和整合从微观控制到宏观规划、从短期适应到长期优化的流动性的认知模型。重要的是，认知模型可以讨论为微观、中观和宏观；这些概念对应于感觉、感知和认知(在神经科学方面)和短期、中期和长期适应(在生态心理学方面)。这说明多足行走需要五种智能功能，表现为1)注意力模块，2)自适应运动控制模块，3)目标识别模块，4)环境地图构建模块，5)最优运动规划模块。所提出的神经认知模型从多个角度整合了这些智能功能。在崎岖地形和动态环境下进行了实时重规划和行为协调实验。结果，所提出的模型已在两个高影响力期刊和两个会议上发表，以及一篇期刊论文正在审查中。

In the third year, we improve the appicability of the proposed neuro-based locomotion generator that has been done in the second year, to more general field of application, especially in interaction with human movement behavior. However, the synchronization between human and lower-limb assistive device has lack in synchronization and active control mechanism. Therefore, a cognitive model is required that can engender and integrate mobility from microscopic control to macroscopic planning and from short-term adaptation to long-term optimization. Importantly, cognitive models can be discussed as micro-, meso-, and macro-scopic; these concepts correspond to sensing, perception, and cognition (in terms of neuroscience) and short-, medium-, and long-term adaptation (in terms of ecological psychology). This suggests that multi-legged locomotion requires five intelligent functions, which manifest as 1) an attention module, 2) an adaptive locomotion control module, 3) an object recognition module, 4) an environmental map building module, and 5) an optimal motion planning module. The proposed neuro-cognitive model integrates these intelligent functions from a multi-scopic point of view. We conducted experiments on real-time re-planning and behavior coordination in rough terrain and dynamic environments level. As the result, the proposed model has been published in two high impact journal and two conferences, and one journal paper under review.