类脑导航的机理、算法、实现与展望

Mechanisms,algorithms,implementation and perspectives of braininspired navigation

脑与神经科学近几十年来的快速发展,初步揭示了动物导航的神经机理。借鉴大脑神经结构及信息处理机制,研究类脑仿生智能导航系统,为复杂环境下低功耗高鲁棒的自主智能导航提供了新的灵感。在详细综述了动物空间导航神经机理基础上,概述探讨了当前机器人仿生类脑导航智能算法,从利用脑启发的神经网络方法处理导航信息实现智能导航的角度,归纳为吸引子神经网络、深度强化学习以及脉冲神经网络等3类算法。接着梳理了类脑导航的实现途径,包括仿生智能传感器和智能类脑处理器平台。最后归纳并展望了类脑导航发展趋势,包括进一步探索生物界导航的脑神经机理及其信息处理过程、细分类脑导航概念内涵、评价指标完善的途径和统一实现框架。

The rapid development of brain and neuroscience in recent decades has initially revealed the neural mechanism of animal navigation.Drawing on the brain neural structures and information processing mechanisms,the study of brain-inspired intelligent navigation systems provides new inspiration for low-power,highly robust autonomous intelligent navigation in complex environments.Based on a detailed review of the neural mechanisms of animal spatial navigation,this paper then outlines and discusses current intelligent algorithms for robotic bionic brain-inspired navigation,which can be categorized into three types according to the three types of neural networks used to process naviga-tion information for intelligent navigation:attractor neural networks,deep reinforcement learning,and spiking neural networks.Then,the ways for implementing brain-inspired navigation,including bionic intelligent sensors and neuromorphic processor platforms,are sorted out.Finally,the development trend of brain-inspired navigation is discussed,including further exploration of the brain neural mechanism of navigation in the biological world and its information pro-cessing process with low energy consumption and high robustness mechanism,subcategorization of the conceptual connotation of brain-inspired navigation,and the ways to improve the evaluation index and the unified implementation framework.