Performance of inverse kinematics analysis of 6 degrees of freedom robotic arm using artificial intelligence methods

Inverse kinematics (IK) is the calculation of joint angles taking into account the orientation and position of the manipulator and is one of the most fundamental problems in robotics. Meta-heuristic algorithms are used to solve complex problems in many areas of engineering. In recent years, meta-heuristic algorithms have begun to be applied to solve the inverse kinematics problem of robot manipulators. The use of swarm intelligence (SI)-based metaheuristic algorithms has increased significantly in many engineering fields. In this study, the position of the end effector of the robotic manipulator was estimated using the newly developed SI-based algorithms Black Widow Optimization Algorithm (BWOA), Whale Optimization Algorithm (WOA) and Dragonfly Algorithm (DA). To prove the success of the tested algorithms, a few randomly selected points in the working area of the robotic manipulator were calculated by changing the 6 joint angles that are the input of the forward kinematics (FK) model. Using the tested algorithms, the optimal angle set providing the target Cartesian coordinates was obtained. In addition, an experimental table was created using the IK model, and IK models were obtained by creating artificial neural network models with the data of this table.