Gravitation Search based Hybrid Algorithm for solving Inverse Kinematics of an n-link Redundant Manipulator

Abstract Inverse kinematics is one of the most complicated problems in robotics. The inverse kinematics calculation is the basis for any industrial robot's ability to plan and follow a trajectory. This paper proposes a hybrid algorithm, e3GSA, based on the Gravitational Search Algorithm for solving the inverse kinematics problem of an n-link redundant robot manipulator. The algorithm's efficiency was evaluated using a fitness function comprising of position error, orientation error, and collision error, and it was found to perform better than the conventional GSA algorithm in simulations. A generalised framework was proposed and tested by simulating a 6-link, 8-link and 12-link robot manipulators. Experimental validation is carried out using a 6-link robot manipulator, which shows that the simulation data are on par with the experimental data. The proposed algorithm was also found to perform adaptively with faster convergence rates and lesser computation time, making it a better choice for other engineering problems that can be transformed into optimization problems.