Machine Learning Control Synthesis by Symbolic Regression for Avoidance of Arbitrary Positioned Obstacles-Reference-Cited by-同舟云学术

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Machine Learning Control Synthesis by Symbolic Regression for Avoidance of Arbitrary Positioned Obstacles

Published:2023-07-03 Issue: Volume: Page:
ISSN:
Container-title:2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)
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Author:

Shmalko Elizaveta¹,Diveev Askhat²

Affiliation:

1. Federal Research Center “Computer Science and Control” of the Rus-sian Academy of Sciences,The Department of Robotics Control,Moscow,Russia,119333

2. Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences' 119333,The Department of Robotics Control,Moscow,Russia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10284032/10284045/10284376.pdf?arnumber=10284376

Reference31 articles.

1. Self calibration of motion and stereo vision for mobile robots;brooks;Robotics and Automation IEEE,1986

2. Real-time obstacle avoidance for manipulators and mobile robots

3. Machine Learning Control by Symbolic Regression

4. The organization of repeller during the motion of mobile robots in environment with obstacles, Mechatronics;pshikhopov;Autom Control,2008

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