This paper explores a 5-degree-of-freedom robotic arm, emphasizing design, simulation, and kinematic analysis. The Denavit–Hartenberg (DH) parameters were meticulously selected to facilitate 180-degree movements, catering to the arm's versatility in pick-up and drop operations. The physical design, executed using SolidWorks, offers valuable insights into practical challenges encountered during fabrication. The implementation in RoboAnalyzer introduces a 5-revolute joint robotic arm, focusing on refining DH parameters for optimal performance. The kinematics analysis, powered by Python, delves into both forward and inverse kinematics. The forward kinematics code determines end-effector positions, whereas the inverse kinematics code computes joint angles, providing a comprehensive understanding of the arm's virtual behavior. Design and fabrication challenges highlight the importance of connecting theoretical concepts to real-world implementation. In conclusion, this integrated approach offers a foundational framework for refining robotic arm designs, addressing implementation challenges, and contributing to advancements in robotics. Ongoing efforts in fabrication and iterative design aim to enhance the arm's practical applicability, making strides toward more robust and adaptable robotic systems.

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Design and Analysis of a 5-DOF Robotic Arm: A RoboAnalyzer Approach

  • Saood Ahmad,
  • Faizan Siddiqui,
  • Saleem Anwar Khan,
  • Abid Ali Khan

摘要

This paper explores a 5-degree-of-freedom robotic arm, emphasizing design, simulation, and kinematic analysis. The Denavit–Hartenberg (DH) parameters were meticulously selected to facilitate 180-degree movements, catering to the arm's versatility in pick-up and drop operations. The physical design, executed using SolidWorks, offers valuable insights into practical challenges encountered during fabrication. The implementation in RoboAnalyzer introduces a 5-revolute joint robotic arm, focusing on refining DH parameters for optimal performance. The kinematics analysis, powered by Python, delves into both forward and inverse kinematics. The forward kinematics code determines end-effector positions, whereas the inverse kinematics code computes joint angles, providing a comprehensive understanding of the arm's virtual behavior. Design and fabrication challenges highlight the importance of connecting theoretical concepts to real-world implementation. In conclusion, this integrated approach offers a foundational framework for refining robotic arm designs, addressing implementation challenges, and contributing to advancements in robotics. Ongoing efforts in fabrication and iterative design aim to enhance the arm's practical applicability, making strides toward more robust and adaptable robotic systems.