Brain-inspired navigation technology, which is derived from the neural mechanisms of the animal brain, demonstrates notable adaptability and energy efficiency. It offers solutions to the shortcomings of conventional analytical navigation systems in complex and dynamic environments. This approach effectively combines spatial cognition and path planning by integrating multimodal information perception, modelling navigation cells, and utilising brain-inspired neural network algorithms. In particular, adaptability plays a central role in enabling systems to cope with environmental variability, sensor uncertainty and unexpected disturbances. However, challenges remain in enhancing information fusion accuracy, system robustness and real-time performance. Future research should emphasise investigating adaptive neural mechanisms in animals to guide the development of biologically plausible and computationally efficient navigation systems that can operate flexibly and reliably in real-world scenarios. • A system-level perspective on adaptive brain-inspired navigation was comprehensively reviewed. • The vestibular–visual–hippocampal circuit was highlighted as a core adaptive mechanism. • Brain-inspired models of navigation cells were analyzed for spatial representation. • Brain-inspired SLAM, planning, and control are discussed in a unified framework. • A feedback-aligned framework was proposed to bridge biology and engineering systems.
Liu et al. (Tue,) studied this question.