Mechatronic design of a planar robot using multiobjective optimization

The concurrent design optimization of robots refers to the problem of optimizing parameters that affects different kinds of features at the same time. For instance, this work presents a study case for the concurrent design optimization of the structure and control of a parallelogram mechanism. The main contribution of this work is the definition of an integrated optimization model that considers two conflicting objectives, defined as the energy and error during a trajectory tracking. In addition, the optimization model considers an error constraint, with the purpose of automatically discarding designs that can not closely follow the trajectory, and the simulation considers a saturation constraint that avoids to deliver torques above a threshold. The multi-objective optimization problem is solved using the Multi-objective Evolutionary Algorithm Based on Decomposition (MOEA/D), the resulting solutions, named Pareto set, are delivered to a final decision maker, to select the adequate design among those with the best compromise between minimum tracking error and energy consumption. A design is a set of lengths and control gains, hence, notice that the control gains are optimized for the corresponding geometry.