论文标题
在英特尔的Loihi上，用于六脚架机器人运动的星形胶质细胞调节的神经形态中央模式发生器
An Astrocyte-Modulated Neuromorphic Central Pattern Generator for Hexapod Robot Locomotion on Intel's Loihi
论文作者
论文摘要
运动对于腿部机器人来说是一个至关重要的挑战，该机器人在自然界中丰富的生物网络“毫不费力”，称为中央模式发生器（CPG）。到目前为止，众多的CPG网络模型成为仿生机器人控制器不适用于新兴的神经形态硬件，从而剥夺了移动机器人的强大步行机制，从而导致固有的能节能系统。在这里，我们提出了一个基于综合的尖峰神经胃网络的脑部型CPG控制器，该网络为六脚架机器人生成了两个步态模式。我们提出的CPG结构以最近确定的星形胶质细胞机制为基础，通过利用芯片和机器人操作系统（ROS）环境之间的实时交互框架，将我们提出的CPG结构无缝整合到英特尔的Loihi神经形态芯片中。在这里，我们证明了loihi-run的CpG可用于控制具有鲁棒性的行走机器人，以对感觉噪声和变化的速度轮廓。我们的结果为在自动移动机器人中的loiihi控制运动范围和其他方法扩展了这种方法。
Locomotion is a crucial challenge for legged robots that is addressed "effortlessly" by biological networks abundant in nature, named central pattern generators (CPG). The multitude of CPG network models that have so far become biomimetic robotic controllers is not applicable to the emerging neuromorphic hardware, depriving mobile robots of a robust walking mechanism that would result in inherently energy-efficient systems. Here, we propose a brain-morphic CPG controler based on a comprehensive spiking neural-astrocytic network that generates two gait patterns for a hexapod robot. Building on the recently identified astrocytic mechanisms for neuromodulation, our proposed CPG architecture is seamlessly integrated into Intel's Loihi neuromorphic chip by leveraging a real-time interaction framework between the chip and the robotic operating system (ROS) environment, that we also propose. Here, we demonstrate that a Loihi-run CPG can be used to control a walking robot with robustness to sensory noise and varying speed profiles. Our results pave the way for scaling this and other approaches towards Loihi-controlled locomotion in autonomous mobile robots.
