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A Bionic Robot Navigation Algorithm Based on Cognitive Mechanism of Hippocampus

机译:基于海马认知机制的仿生机器人导航算法

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The firing of space cell in hippocampus is considered to be able to form an intrinsic map for the environment which is called cognitive map. Previous bionic navigation algorithms (such as rat simultaneous localization and mapping) and traditional SLAM algorithms lack sufficient physiological basis and cannot reflect the cognitive mechanism of hippocampal formation. Based on the cognitive mechanism of hippocampal space cells, this paper proposes a navigation algorithm for constructing accurate environmental cognitive map. This algorithm is characterized by the construction of a unified spatial cell attractor model for self-motion trajectory path integration. The expressions of grid cells and place cells are driven by stripe cells. The algorithm performs closed-loop detection by collecting depth image, red green blue+depthmap information and corrects the error of spatial cells' path integral. Eventually, we get a precise cognitive map of the environment and bionic robot navigation is achieved by global navigation and local navigation algorithm based on the map. The cognitive map is a topological metric map that contains the topological relations of the environment feature point coordinates, visual cues, and specific sites. In this paper, the method is verified by the simulation experiment and the physical experiment on the robot platform. The research results laid the foundation for the research of the robot navigation method based on the hippocampus cognitive mechanism. Note to Practitioners Environmental cognition and navigation ability are the main function of intelligent mobile robots. People and animals have strong adaptability and cognitive ability in unfamiliar environment, and they can independently recognize and navigate in unfamiliar environment. Now, the environmental cognition and navigation ability of intelligent robots are far from the level of human and animal. This paper suggests a bionic robot navigation algorithm based on the cognitive mechanism of rat hippocampus. The bionic robot navigation algorithm makes mobile robots more intelligent by learning and imitating human and animal's environmental cognition and navigation ability. This navigation algorithm conforms to the physiological characteristics and is pretty accurate and intelligent. The experimental results demonstrate the effectiveness of this algorithm in building environment map and navigation.
机译:海马中的空间细胞的发射被认为能够形成环境的固有图,称为认知图。以前的仿生导航算法(例如大鼠同时定位和映射)和传统的SLAM算法缺乏足够的生理基础,无法反映海马形成的认知机制。基于海马空间细胞的认知机制,提出了一种构建精确环境认知图的导航算法。该算法的特征在于构建用于自运动轨迹路径整合的统一空间单元吸引子模型。网格单元格和位置单元格的表达由条纹单元格驱动。该算法通过收集深度图像,红色,绿色,蓝色和深度图信息进行闭环检测,并校正空间像元路径积分的误差。最终,我们获得了精确的环境认知地图,仿生机器人导航是通过基于地图的全局导航和局部导航算法实现的。认知图是一种拓扑度量图,其中包含环境特征点坐标,视觉提示和特定位置的拓扑关系。本文通过在机器人平台上的仿真实验和物理实验对方法进行了验证。研究成果为基于海马认知机制的机器人导航方法的研究奠定了基础。给从业者的注意事项环境认知和导航能力是智能移动机器人的主要功能。人和动物在陌生的环境中具有很强的适应能力和认知能力,可以在陌生的环境中独立地识别和导航。现在,智能机器人的环境认知和导航能力已经远远超过了人类和动物的水平。本文提出了一种基于大鼠海马认知机制的仿生机器人导航算法。仿生机器人导航算法通过学习和模仿人类和动物对环境的认知和导航能力,使移动机器人更加智能。该导航算法符合生理特征,非常准确和智能。实验结果证明了该算法在建筑环境地图导航中的有效性。

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