Empirical evaluation of common contact models for planar impact

In this paper we evaluate the predictive performance of six commonly used rigid body impact models on real planar impacts captured with a motion tracking system. We propose a metric to evaluate the performance of impact models on a task (based on predicting post impact momentum) and use this metric to tune the six parametric models. We evaluate model performance in predicting impact outcomes against the defined metric and discuss the implications of uncertainty in geometric models and initial conditions. We show that the models can fairly effectively predict the outcomes of single impacts on our chosen task. We motivate further study into consensus and hybrid impact models by showing that a hypothetical hybrid model would significantly outperform the isolated models by providing a post-hoc model that demonstrates an upper bound on the combined predictive power of the models. We use perturbation analysis to compute the predictive range of the models and show that bifurcations can cause the model predictions to cluster into regions of the state space.