A Positioning Method Based on Place Cells and Head-Direction Cells for Inertial/Visual Brain-Inspired Navigation System.

Yudi Chen, Zhi Xiong, Jianye Liu, Chuang Yang, Lijun Chao, Yang Peng

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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Authors and funding

6 authors.

Yudi ChenNavigation Research Center, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Zhi XiongNavigation Research Center, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Jianye LiuNavigation Research Center, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Chuang YangNavigation Research Center, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Lijun ChaoNavigation Research Center, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

Yang PengShanghai Aerospace Control Technology Institute, Shanghai 201108, China.

Funding

Aeronautic Science Foundation of China ASFC-2020Z071052001Foundation Research Project of Jiangsu Province (The Natural Science Fund of Jiangsu Province) BK20181291Introduction plan of high end experts G20200010142National Defense Basic Research Program JCKY2020605C009National Natural Science Foundation of China 61873125National Natural Science Foundation of China 62073163Supported by Shanghai Aerospace Science and Technology Innovation Fund SAST2019-085Support for projects in special zones for national defense science and technology innovation, advanced research project of the equipment development 30102080101the 111 Project B20007the Fundamental Research Funds for the Central Universities NZ2020004

6 · The paper itself

Abstract

Mammals rely on vision and self-motion information in nature to distinguish directions and navigate accurately and stably. Inspired by the mammalian brain neurons to represent the spatial environment, the brain-inspired positioning method based on multi-sensors' input is proposed to solve the problem of accurate navigation in the absence of satellite signals. In the research related to the application of brain-inspired engineering, it is not common to fuse various sensor information to improve positioning accuracy and decode navigation parameters from the encoded information of the brain-inspired model. Therefore, this paper establishes the head-direction cell model and the place cell model with application potential based on continuous attractor neural networks (CANNs) to encode visual and inertial input information, and then decodes the direction and position according to the population neuron firing response. The experimental results confirm that the brain-inspired navigation model integrates a variety of information, outputs more accurate and stable navigation parameters, and generates motion paths. The proposed model promotes the effective development of brain-inspired navigation research.

Indexed as

Place CellsAnimalsBrainHeadNeural Networks, ComputerNeuronsbrain-inspired navigationcontinuous attractor neural networks (CANNs)head-direction cellsplace cellspopulation neuron decoding

Identifiers

PMID34883992

DOI10.3390/s21237988

PMCPMC8659458

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.