Robot Arm Trajectory Synthesis Based on Metaheuristic Optimization Techniques

In this work a two-arm robot synthesis is of scope. A set of parameters have been considered in the mechanism’s synthesis, mainly the links lengths and masses. A set of target trajectories have been set for the two links’ extremity to be fulfilled. For the sake of enhanced accuracy, the system’s trajectories feeding back the optimization process have been obtained by means of the system’s equation of motion. Therefore, the effects of changes in mass can be taken into account in sharp contrast with what is done in kinematic synthesis. To this end, metaheuristic optimization mainly, Genetic Algorithm, Particle Swarm Optimization, Differential Evolution, Artificial Bee Colony, Ant Colony, Simulating Annealing and Imperialist Competitive Algorithm techniques have been implemented to investigate their performance solving similar problems. It has been proven that some of the techniques are more burdened to reach out an accurate solution than others. The implemented optimization approach efficiency has been confirmed through numerical simulation.