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- W3157913551 abstract "It is necessary to control the movement of a complex multi-joint structure such as a robotic arm in order to reach a target position accurately in various applications. In this paper, a hybrid optimal Genetic–Swarm solution for the Inverse Kinematic (IK) solution of a robotic arm is presented. Each joint is controlled by Proportional–Integral–Derivative (PID) controller optimized with the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), called Genetic–Swarm Optimization (GSO). GSO solves the IK of each joint while the dynamic model is determined by the Lagrangian. The tuning of the PID is defined as an optimization problem and is solved by PSO for the simulated model in a virtual environment. A Graphical User Interface has been developed as a front-end application. Based on the combination of hybrid optimal GSO and PID control, it is ascertained that the system works efficiently. Finally, we compare the hybrid optimal GSO with conventional optimization methods by statistic analysis." @default.
- W3157913551 created "2021-05-10" @default.
- W3157913551 creator A5018919535 @default.
- W3157913551 creator A5086016863 @default.
- W3157913551 date "2021-05-03" @default.
- W3157913551 modified "2023-09-24" @default.
- W3157913551 title "Intelligent Trajectory Tracking Behavior of a Multi-Joint Robotic Arm via Genetic–Swarm Optimization for the Inverse Kinematic Solution" @default.
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- W3157913551 doi "https://doi.org/10.3390/s21093171" @default.
- W3157913551 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8124729" @default.
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