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What are the common numerical methods used in solving inverse kinematics problems for robotic arms? 


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Inverse kinematics problems for robotic arms are commonly solved using numerical methods. One approach is the use of iterative numerical methods, such as the Newton-Raphson or Jacobian inverse methods, which calculate the joint variables iteratively to move the end-effector to the desired position and orientation . Another approach is the use of lookup tables, where a table is built to output a joint configuration that can move the end-effector close to the target position, reducing the number of iterations required for the numerical method . Additionally, machine learning methods, such as neural networks with back-propagation algorithms, have been proposed to solve the inverse kinematics problem numerically with acceptable accuracy and precision .

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The paper does not mention the common numerical methods used in solving inverse kinematics problems for robotic arms.
The paper does not mention the common numerical methods used in solving inverse kinematics problems for robotic arms.
The paper does not mention the common numerical methods used in solving inverse kinematics problems for robotic arms.
The paper mentions that when analytical inverse kinematics solvers are not possible, numerical methods such as Newton-Raphson or Jacobian inverse can be used to solve the inverse kinematics problem for robotic arms.
The provided paper does not mention the common numerical methods used in solving inverse kinematics problems for robotic arms.

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