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Combined improved A and greedy algorithm for path planning of multi-objective mobile robot
by
Xiang, Dan
, Lin, Hanxi
, Huang, Dan
, Ouyang, Jian
in
639/166
/ 639/4077
/ Algorithms
/ Artificial intelligence
/ Automation
/ Energy consumption
/ Heuristic
/ Humanities and Social Sciences
/ multidisciplinary
/ Optimization
/ Planning
/ Robots
/ Science
/ Science (multidisciplinary)
2022
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Combined improved A and greedy algorithm for path planning of multi-objective mobile robot
by
Xiang, Dan
, Lin, Hanxi
, Huang, Dan
, Ouyang, Jian
in
639/166
/ 639/4077
/ Algorithms
/ Artificial intelligence
/ Automation
/ Energy consumption
/ Heuristic
/ Humanities and Social Sciences
/ multidisciplinary
/ Optimization
/ Planning
/ Robots
/ Science
/ Science (multidisciplinary)
2022
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Do you wish to request the book?
Combined improved A and greedy algorithm for path planning of multi-objective mobile robot
by
Xiang, Dan
, Lin, Hanxi
, Huang, Dan
, Ouyang, Jian
in
639/166
/ 639/4077
/ Algorithms
/ Artificial intelligence
/ Automation
/ Energy consumption
/ Heuristic
/ Humanities and Social Sciences
/ multidisciplinary
/ Optimization
/ Planning
/ Robots
/ Science
/ Science (multidisciplinary)
2022
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Combined improved A and greedy algorithm for path planning of multi-objective mobile robot
Journal Article
Combined improved A and greedy algorithm for path planning of multi-objective mobile robot
2022
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Overview
With the development of artificial intelligence, path planning of Autonomous Mobile Robot (AMR) has been a research hotspot in recent years. This paper proposes the improved A* algorithm combined with the greedy algorithm for a multi-objective path planning strategy. Firstly, the evaluation function is improved to make the convergence of A* algorithm faster. Secondly, the unnecessary nodes of the A* algorithm are removed, meanwhile only the necessary inflection points are retained for path planning. Thirdly, the improved A* algorithm combined with the greedy algorithm is applied to multi-objective point planning. Finally, path planning is performed for five target nodes in a warehouse environment to compare path lengths, turn angles and other parameters. The simulation results show that the proposed algorithm is smoother and the path length is reduced by about 5%. The results show that the proposed method can reduce a certain path length.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
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