In this work, a planar cable parallel robot (CPR) driven by four cable-and-pulley differentials is proposed and analyzed. A new cable-and-pulley differential is designed by adding an extra pulley to eliminate the modeling inaccuracies due to the pulley radius and obviate the need of solving the complex model which considers the pulley kinematics. The design parameters of the proposed CPR are determined through multi-objective optimal design for the largest total orientation wrench closure workspace (TOWCW) and the highest global stiffness magnitude index. The proposed differentially driven CPR is evaluated by comparing various performance indices with a fully actuated CPR.
In this paper, we present a novel approach for bipedal walking pattern generation. The proposed method is designed based on 2D inverted pendulum model. All control variables are optimized for an energy efficient gait. To obviate the need of solving non-linear dynamics on-line, a deep neural network is adopted for fast non-linear mapping from desired states to control variables. Normalized dimensionless data is generated to train the neural network, therefore, the trained neural network can be applied to bipedal robots of any size, without any specific modification. The proposed method is later verified through numerical simulations. Simulation results demonstrated that the proposed approach can generate feasible walking motions, and regulate robot's walking velocity successfully. Its disturbance rejection capability was also validated.
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