Decision Tree Algorithm and Deep Learning Technology Based Motion Decision Algorithm for Autonomous Robots
Authors: 
Chenxi Jiang, Yayan LeiAuthors Info & Claims
Article No.: 19, Pages 1 - 6
Abstract
The current motion decision of autonomous robots is characterised by rigid motion commands, which leads to unsatisfactory motion decision results. To this end, an autonomous robot motion decision algorithm based on decision tree algorithm and deep learning technology is proposed. A robust combinatorial controller is set up for the autonomous robot. The motion control commands are modified based on the decision tree algorithm, and a disturbance estimation compensation term is added.Based on deep learning technology, autonomous robot motion decision-making is trained, obstacle avoidance correction is performed on motion control commands, and ultimately an autonomous robot motion decision-making algorithm is generated. Experiments show that the results of the algorithm has overlap with the optimal motion path by 96.49%, and the decision results are of high quality and have high practical application value.
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- Decision Tree Algorithm and Deep Learning Technology Based Motion Decision Algorithm for Autonomous Robots
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Published In
August 2023
378 pages
ISBN:9798400708701
DOI:10.1145/3627341
Copyright © 2023 ACM.
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Association for Computing Machinery
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Published: 15 December 2023
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ICCVIT 2023
ICCVIT 2023: International Conference on Computer, Vision and Intelligent Technology
August 25 - 28, 2023
Chenzhou, China
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ICCVIT '23 Paper Acceptance Rate 54 of 142 submissions, 38%;
Overall Acceptance Rate 54 of 142 submissions, 38%
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