Cash Collection Model of Electric Power Business Office Based on Computer Algorithm

With the continuous development of intelligent algorithms, mobile robot (hereinafter referred to as MR) technology is gradually mature, which has been widely used in a variety of industries, such as industry, agriculture, medical treatment, service and so on. With the improvement of intelligent leve...

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Veröffentlicht in:Journal of physics. Conference series Jg. 2146; H. 1; S. 12023 - 12028
Hauptverfasser: Guo, Binghua, Guo, Nan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bristol IOP Publishing 01.01.2022
Schlagworte:
Algorithms
Dynamic Obstacle Avoidance Algorithm
Kinematics
Mobile Robot
Obstacle avoidance
Optimization
Path Planning
Physics
Robots
ISSN:1742-6588, 1742-6596
Online-Zugang:Volltext
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Zusammenfassung:With the continuous development of intelligent algorithms, mobile robot (hereinafter referred to as MR) technology is gradually mature, which has been widely used in a variety of industries, such as industry, agriculture, medical treatment, service and so on. With the improvement of intelligent level, people have higher and higher requirements for MRs, which requires MRs to constantly adapt to different environments, especially dynamic environments. In the dynamic environment, obstacle avoidance technology has become the focus of intelligent robot research, which needs to continuously develop a variety of algorithms. By combining a variety of algorithms, we can realize obstacle avoidance and PP (hereinafter referred to as PP) of MR, which can realize obstacle avoidance more efficiently, in real time and intelligently. Multi algorithm fusion of MR has become the main trend of obstacle avoidance in the future, which will realize PP and optimization. Firstly, this paper analyzes the differences between traditional algorithms and intelligent algorithms. Then, the kinematics model and PP algorithm of MR are analyzed. Finally, the simulation is carried out.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2146/1/012023