code underlying publication: Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee

DOI:10.4121/71bb6fd6-0983-442c-a266-fe3b7bee77e4.v1
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DOI: 10.4121/71bb6fd6-0983-442c-a266-fe3b7bee77e4

Datacite citation style

Tang, Yujie; Hu, Liang; Zhou, Zhipeng; Pan, Wei (2024): code underlying publication: Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/71bb6fd6-0983-442c-a266-fe3b7bee77e4.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This collection contains all code to produce the results of "Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee," 2021 IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 2021, pp. 10243-10249, doi: 10.1109/ICRA48506.2021.9561440. This paper presents a deep reinforcement learning (DRL) algorithm for orientation estimation using inertial sensors combined with a magnetometer. To the best of our knowledge, this is the first DRL-based orientation estimation method using inertial sensors combined with a magnetometer. The code is written in Python. The packages used are listed in "requirements.txt". To reproduce the code, please refer to "README.md".

History

  • 2024-10-29 first online, published, posted

Publisher

4TU.ResearchData

Format

.py

Organizations

TU Delft, Faculty of Mechanical Engineering, Department of Cognitive robotics

DATA

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