# Calibration of Mobile Robots Using ATOM

## TL;DR

This paper introduces ATOM, a new method for calibrating mobile robots with multiple sensors, improving accuracy even with imprecise localization.

## Contribution

A novel calibration framework, ATOM, that simultaneously estimates sensor poses and calibration patterns for multi-sensor robotic systems.

## Key findings

- ATOM improves calibration accuracy for mobile manipulators with diverse sensor modalities.
- The method was validated through simulations and real-world experiments.
- ATOM handles imprecise localization systems effectively.

## Abstract

The calibration of mobile manipulators requires accurate estimation of both the transformations provided by the localization system and the transformations between sensors and the motion coordinate system. Current works offer limited flexibility when dealing with mobile robotic systems with many different sensor modalities. In this work, we propose a calibration approach that simultaneously estimates these transformations, enabling precise calibration even when the localization system is imprecise. This approach is integrated into Atomic Transformations Optimization Method (ATOM), a versatile calibration framework designed for multi-sensor, multi-modal robotic systems. By formulating calibration as an extended optimization problem, ATOM estimates both sensor poses and calibration pattern positions. The proposed methodology is validated through simulations and real-world case studies, demonstrating its effectiveness in improving calibration accuracy for mobile manipulators equipped with diverse sensor modalities.