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Robot Motion Control Using Stepping Ahead Firefly Algorithm and Kinematic Equations

delete2024-01-01
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OA
AI
K
Kaylash Chaudhary *
A
Alvin Prasad
A
Avinesh Prasad
B
Bibhya Sharma
DOI:10.1109/ACCESS.2024.3380004delete
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摘要

摘要

En 中文
The use of robots to carry out activities in various fields has evolved over the years. Robots can move from one location to another according to a plan and have a good understanding of the environment to perform their assigned tasks. Robot movements are based on motion planning and control algorithms. This paper proposes a new hybrid motion planning and control algorithm called FAStep-Kinematic (Stepping Ahead Firefly algorithm and Kinematic equations). This algorithm includes the Firefly Stepping Ahead algorithm to avoid obstacles, the equation of motion to control the movement of the robot, and a method to detect obstacles. The algorithm starts with the equation of motion and switches to the stepping ahead firefly algorithm when an obstacle is detected. The stepping ahead firefly algorithm then plans the robot's next step to avoid obstacles. The robot moves to this step. This procedure is repeated until the robot successfully avoids an obstacle and reaches its target. The obstacles used in this article are static and are known to robots. The hybrid algorithm will be used to navigate robots in a cluttered environment. The new algorithm's effectiveness will be seen with an application to tractor-trailer robotic systems. The results show that the robots are able to reach their destination safely and using a shorter route. Additionally, this research compared the new hybrid algorithm's performance with that of the ACO-Kinematic (Ant Colony Optimization and Kinematic equations) algorithm in terms of path length and convergence time. The analysis show that the hybrid algorithm is superior to the ACO-Kinematic algorithm. The proposed algorithm improves the path length by 0.37%, 9.22%, and 5.79% compared to the ACO-Kinematic algorithm in three different scenarios.
Keyword:
Robot
motion
control
optimization
algorithm

期刊

IEEE Access 封面图
IEEE Access
IF:
3.6
论文数:
9.8W
被引数:
29.4W

机构

U
University of the South Pacific
学者数:
932
论文数: 777
被引数: 899
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