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Robotics have become very useful and meaningful in industrial automation, so their designing and controlling are much-considered factors. Robots, as a complicated system, must detect and be able to solve the required problem with great perfection and accuracy. To be able to solve the required task, robot must work with good certainty and it must be flawless in nature. This analysis shows the robot arm trajectory planning which will be solved by using Forward and Inverse Kinematics Principles with using ANFIS networks. Providing a solution to the IK problem is very useful step as it will decide the location of the gripper where the required task will be performed. To solve FK and IK problems, MATLAB was used and the results are compared to both analytical approach and ANFIS method. ANFIS is a mix of both NN and Fuzzy logic. ANFIS was used to train the data provided by the FK problem, to give more certainty and fidelity to the required joint angles mapping for the degree-of-freedom robotic arm.

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Kinematic Modeling of 4R-Robotic Arm Using Adaptive Neuro-Fuzzy Inference System

  • 会议论文

  • 发表日期：

    2025年

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  • Ajay Sharma,
  • Shubhra Dixit,
  • Manju Kashyap,
  • Surbhi Gupta

摘要

Robotics have become very useful and meaningful in industrial automation, so their designing and controlling are much-considered factors. Robots, as a complicated system, must detect and be able to solve the required problem with great perfection and accuracy. To be able to solve the required task, robot must work with good certainty and it must be flawless in nature. This analysis shows the robot arm trajectory planning which will be solved by using Forward and Inverse Kinematics Principles with using ANFIS networks. Providing a solution to the IK problem is very useful step as it will decide the location of the gripper where the required task will be performed. To solve FK and IK problems, MATLAB was used and the results are compared to both analytical approach and ANFIS method. ANFIS is a mix of both NN and Fuzzy logic. ANFIS was used to train the data provided by the FK problem, to give more certainty and fidelity to the required joint angles mapping for the degree-of-freedom robotic arm.