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Comparative Study of Inverse Kinematics Using Data Driven And FABRIK Approach

One of the most important problem in the field of robotics is solving the inverse kinematics. Various analytical, iterative and data driven techniques have already been proposed for solving this problem. But there is still a debate on which approach provides a better performance, reliability and requires low computation. So, in this paper we provide a performance comparison between two such techniques- FABRIK (Forward And Backward Reaching Inverse Kinematics) and neural network based approach, for solving Inverse Kinematics. The performance is analysed using a 3-link planar manipulator.