Active Planar Mass Distribution Estimation with Robotic Manipulation

Abstract

In this work, we present a method to estimate the planar mass distribution of a rigid object through robotic interactions and force/torque feedback. This is a challenging problem because of the complexity of modeling physical dynamics and the action dependencies across the model parameters. We propose a sequential estimation strategy combined with a set of robot action selection rules based on the analytical formulation of a discrete-time dynamics model. To evaluate the performance of our approach, we also manufactured re-configurable block objects that allow us to modify the object mass distribution while having access to the ground truth values. We compare our approach against multiple baselines and show that it can estimate the mass distribution with around 10% error, while the baselines have errors ranging from 18% to 68%.