Robot Human-Lateral-Following Method with Adaptive Linear Quadratic Regulator
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 14274 LNAI, Page: 130-141
2023
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Conference Paper Description
For following robots in a human-machine cooperative context, a lateral following method based on Adaptive Linear Quadratic Regulator (ALQR) control method is proposed in this paper. Compared to conventional following techniques, this method is more adaptable and may be used in a variety of contexts. First, Non-Uniform Rational B-Splines (NURBS) curves are employed to enhance the lateral following theoretical trajectory of the robot. Further, fuzzy control is used to optimize the traditional LQR controller. Finally, experiments are carried out to verify the reliability of the ALQR algorithm. The experimental results show that the lateral following method proposed in this paper is improved compared with other algorithms. The real-time performance of forward error and lateral error is improved by 43.9% and 62.1% respectively. In terms of stability, it increased by 55.2% and 71.8% respectively.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85175958167&origin=inward; http://dx.doi.org/10.1007/978-981-99-6501-4_12; https://link.springer.com/10.1007/978-981-99-6501-4_12; https://dx.doi.org/10.1007/978-981-99-6501-4_12; https://link.springer.com/chapter/10.1007/978-981-99-6501-4_12
Springer Science and Business Media LLC
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