In this paper, robotic systems when two or more underactuated manipulators are working in a cooperative way are studied. The underactuation effects on object to be controlled and on load capacity of the cooperative arms are analyzed. A hybrid control of motion and squeeze force is proposed. For the motion control, a Jacobian matrix that relates the torques in the actuated joints to the resulting force in the load is obtained. In addition, a method to compute the dynamic load-carrying capacity of cooperative manipulators with passive joints is presented. Results of the control system are verified in simulations and in an actual system formed by two cooperative arms.

The NK hybrid genetic algorithm for clustering is proposed in this paper. In order to evaluate the solutions, the hybrid algorithm uses the NK clustering validation criterion 2 (NKCV2). NKCV2 uses information about the disposition of N small groups of objects. Each group is composed of K+1 objects of the dataset. Experimental results show that density-based regions can be identified by using NKCV2 with fixed small K. In NKCV2, the relationship between decision variables is known, which in turn allows us to apply gray box optimization. Mutation operators, a partition crossover, and a local search strategy are proposed, all using information about the relationship between decision variables. In partition crossover, the evaluation function is decomposed into q independent components; partition crossover then deterministically returns the best among 2q possible offspring with computational complexity O(N). The NK hybrid genetic algorithm allows the detection of clusters with arbitrary shapes and the automatic estimation of the number of clusters. In the experiments, the NK hybrid genetic algorithm produced very good results when compared to another genetic algorithm approach and to state-of-art clustering algorithms.