Generating manipulator trajectories considering multiple objectives and obstacle avoidance is a non trivial optimization problem. In this paper a multiobjective genetic algorithm is proposed to address this problem. Multiple criteria are optimized up to five simultaneous objectives. Simulations results are presented for robots with two and three degrees of freedom, considering two and five objectives optimization. A subsequent analysis of the solutions distribution along the converged non-dominated Pareto front is carried out, in terms of the achieved diversity.