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Enhanced Center Constraint Weighted A Algorithm for Path Planning of Petrochemical Inspection Robot
by
Chambers, Jonathon
, Li, JiaHe
, Lai, Xin
in
Algorithms
/ Artificial Intelligence
/ Control
/ Electrical Engineering
/ Engineering
/ Heuristic
/ Inspection
/ Mechanical Engineering
/ Mechatronics
/ Nodes
/ Path planning
/ Petroleum chemicals industry
/ Response time
/ Robotics
/ Robots
/ Search process
/ Short Paper
/ Shortest path planning
2021
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Enhanced Center Constraint Weighted A Algorithm for Path Planning of Petrochemical Inspection Robot
by
Chambers, Jonathon
, Li, JiaHe
, Lai, Xin
in
Algorithms
/ Artificial Intelligence
/ Control
/ Electrical Engineering
/ Engineering
/ Heuristic
/ Inspection
/ Mechanical Engineering
/ Mechatronics
/ Nodes
/ Path planning
/ Petroleum chemicals industry
/ Response time
/ Robotics
/ Robots
/ Search process
/ Short Paper
/ Shortest path planning
2021
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Enhanced Center Constraint Weighted A Algorithm for Path Planning of Petrochemical Inspection Robot
by
Chambers, Jonathon
, Li, JiaHe
, Lai, Xin
in
Algorithms
/ Artificial Intelligence
/ Control
/ Electrical Engineering
/ Engineering
/ Heuristic
/ Inspection
/ Mechanical Engineering
/ Mechatronics
/ Nodes
/ Path planning
/ Petroleum chemicals industry
/ Response time
/ Robotics
/ Robots
/ Search process
/ Short Paper
/ Shortest path planning
2021
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Enhanced Center Constraint Weighted A Algorithm for Path Planning of Petrochemical Inspection Robot
Journal Article
Enhanced Center Constraint Weighted A Algorithm for Path Planning of Petrochemical Inspection Robot
2021
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Overview
In many practical applications of robot path planning, finding the shortest path is critical, while the response time is often overlooked but important. To address the problems of search node divergence and long calculation time in the A* routing algorithm in the large scenario, this paper presents a novel center constraint weighted A* algorithm (CCWA*). The heuristic function is modified to give different dynamic weights to nodes in different positions, and the node weights are changed in the specified direction during the expansion process, thereby reducing the number of search nodes. An adaptive threshold is further added to the heuristic function to enhance the adaptiveness of the algorithm. To verify the effectiveness of the CCWA* algorithm, simulations are performed on 2-dimensional grid maps of different sizes. The results show that the proposed algorithm speeds up the search process and reduces the planning time in the process of path planning in a multi-obstacle environment compared with the conventional A* algorithm and weighted A* algorithm.
Publisher
Springer Netherlands,Springer,Springer Nature B.V
Subject
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