Prediction of Inverse Kinematics for a 6-DOF Industrial Robot Arm Using Soft Computing Techniques

In this twenty-first century, due to the heavy demand for high quality and great accuracy product from the customer, a large number of industries nowadays shifted their focus toward the installation of the robotic arm in their assembly line for faster production of the product. One of the most challenging problems of the robotic system is the inverse kinematics which deals to find the joint angles for the given robotic configurations. When the DOF of the system increases, it is very difficult to calculate the precise result with the help of the analytical methods and also the computing time taken for solving the analytical methods of the robotic systems is more. So, to achieve a better result for the inverse kinematics problem various intelligent and nontraditional techniques are used in recent years. In this article, authors have presented the application of soft computing techniques to obtain the inverse kinematics of Kawasaki RS06L 6-DOF robotic manipulator for a pick and place operation. For validating and checking the efficiency of the proposed approaches, a comprehensive study has been conducted among the techniques such as artificial bee colony (ABC), firefly algorithm (FA), invasive weed optimization (IWO), and particle swarm optimization (PSO). In a simulation environment, a thorough study conducted to find the inverse kinematics of the proposed system before the actual experimentation, and obtained results are fed into the Kawasaki Controller for the pick and place task which shows efficient results.

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