A Comparative Analysis of Contact Models in Trajectory Optimization for Manipulation
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In this paper, we analyze the effects of the contact model on contact-implicit trajectory optimization for manipulation. We consider three different cases: (1) a contact model that is based on complementarity constraints, (2) a smooth contact model, and our proposed method (3) a variable smooth contact model. We compare these models in simulation in terms of quality of motions discovered, physical accuracy, and computation time. In each case, optimization is initialized by setting all decision variables to zero, namely, without a meaningful initial guess. For simulations, we consider a pushing manipulation task with varying complexity for a 7 degrees-of-freedom robot arm. Our results demonstrate that the optimization based on the proposed variable smooth contact model provides a good trade-off between the physical fidelity and the quality of motions discovered at the cost of increased computation time.
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