  Collaborative robotic industrial cells are workspaces where robots
collaborate with human operators. In this context, safety is paramount, and for
that a complete perception of the space where the collaborative robot is
inserted is necessary. To ensure this, collaborative cells are equipped with a
large set of sensors of multiple modalities, covering the entire work volume.
However, the fusion of information from all these sensors requires an accurate
extrinsic calibration. The calibration of such complex systems is challenging,
due to the number of sensors and modalities, and also due to the small
overlapping fields of view between the sensors, which are positioned to capture
different viewpoints of the cell. This paper proposes a sensor to pattern
methodology that can calibrate a complex system such as a collaborative cell in
a single optimization procedure. Our methodology can tackle RGB and Depth
cameras, as well as LiDARs. Results show that our methodology is able to
accurately calibrate a collaborative cell containing three RGB cameras, a depth
camera and three 3D LiDARs.
