Calibrating Mixed Reality for Scalable Multi-Robot Experiments

Abstract

When testing multi-robot teams, researchers are often forced to make a choice: test on real robots (where fidelity is high, but the number of actual robots is low) or test in simulation (where fidelity is low, but the number of robots can be large). This problem is acute for robots with sophisticated sensing and planning systems, where the cost of the robots rises in concert with their need for more realistic environments. We propose a mixed-reality testing framework in which real robots interact with virtual counterparts, allowing a large number of robots to interact in the environment with high fidelity. However, this creates a new problem: the simulated robots must behave like their real teammates. We consider the problem of calibrating the parameters of virtual robots so that the results of a mixed-reality experiment are representative of the performance of a real robotic team. In particular, we use virtual robots to elicit behaviors from physical robots in order to empirically measure their kino-dynamic characteristics.