An Efficient Robotic Manipulator Trajectory Planning Using Modified Firefly Algorithm

Abstract

A novel modified firefly algorithm (MFA) for optimal and accurate robotic trajectory planning has been proposed in this paper. In order to demonstrate the entire trajectory planning problem, an industrial 4-DOF SCARA robot manipulator has been chosen. An error function which is a combination of both error in position and error in orientation coordinates is defined as total objective function for the trajectory optimization assignment. In order to accomplish an efficient optimal trajectory, the best cost of the error objective fitness function, algorithm convergence speed, the error in positions and orientations are chosen as performance parameters. The objective function has been executed using bat algorithm (BA), cuckoo-search algorithm (CS), firefly algorithm (FA), artificial bee colony (ABC) algorithm and the proposed MFA. The effectiveness of the proposed MFA is validated by carrying out a comparative review of the acquired trajectory results from the MFA against the other considered existing algorithms. The ranks of the algorithms have been evaluated by conducting Friedman test for the mean solutions of error in positions and orientation. The comparative study of the implemented algorithms shows that MFA executes superior to the other algorithms with less computational effort for the same boundary conditions.