Construction and validation of a high fidelity simulator for a planar range sensor

We study the problem of building a sensor model for the purpose of simulation. Our work is motivated by the potential impact of realistic simulators on the development cycle of software for real robots. The case is made for building models from approximate state information, relieving the burden of ground truth. Unlike calibration, where the goal is to identify and remove error from a signal, our aim to reproduce the signal in its entirety, including its error properties. Instead of physically modeling sensor behavior, a data-driven approach is taken. The implementation of our approach to simulate a simple but noisy laser rangefinder is described. Finally, approaches to validate the simulator are discussed. We compare not only raw sensor predictions, but also overall performance of algorithms on simulated versus real data.