IMU Dead-Reckoning Localization with RNN-IEKF Algorithm-Reference-Cited by-同舟云学术

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IMU Dead-Reckoning Localization with RNN-IEKF Algorithm

Published:2022-10-23 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
language:
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Author:

Zhou Hang¹,Zhao Yibo¹,Xiong Xiaogang¹,Lou Yunjiang¹,Kamal Shyam²

Affiliation:

1. Harbin Institute of Technology Shenzhen,Shenzhen,P.R. China,518055

2. Indian Institute of Technology (BHU),Varanasi,Uttar Pradesh,India

Funder

Shenzhen Science and Technology Programs

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9981026/9981028/09982087.pdf?arnumber=9982087

Reference20 articles.

1. Vision meets robotics: The KITTI dataset

2. AI-IMU Dead-Reckoning

3. Long Short-Term Memory Kalman Filters: Recurrent Neural Estimators for Pose Regularization

4. RL-AKF: An Adaptive Kalman Filter Navigation Algorithm Based on Reinforcement Learning for Ground Vehicles

5. Kalman filtering with state constraints: a survey of linear and nonlinear algorithms

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Region-determined localization method for unmanned ground vehicle under pole-like feature environment;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

2. Unmanned aerial vehicle localization using angle of departure from a single base station and dead‐reckoning;Electronics Letters;2024-01

3. Model-Based Deep Learning for Low-Cost IMU Dead Reckoning of Wheeled Mobile Robot;IEEE Transactions on Industrial Electronics;2024

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