Development of an AUV calibration framework

In order to increase accuracy and robustness of their state and pose estimations, Autonomous Underwater Vehicles (AUVs) use a growing number of sensors. All these sensors must be calibrated before being used. This calibration step is essential in order to receive the most reliable data possible: Without a good calibration, one AUV can get untrustworthy data and, as worst-case consequences, make decision that leads to a fatal collision or to a loss of the robot.

Currently, several AUVs at the DFKI RIC use hard-coded poses or tuning parameters for sensors. These parameters can be taken, for example, from the sensor manufacturer or from the Computer-Aided Design (CAD) model. This means firstly that one cannot be sure that these poses/parameters are accurate and on the other hand, these values must be manually adapted whenever there are changes in the AUV-hardware. On the top of that, there is currently no framework at the DFKI that automatically calibrates sensors AUV-independently. This leads to the fact that some calibration functions might be reimplemented from scratch, even if there are already existing functions written as part of other projects.

The goal of this master thesis is to create a pose calibration framework for AUVs. That would make possible, for one, based on defined experiments, to estimate the relative poses, biases and other static parameters of sensors, independently of an AUV.

In der Regel sind die Vorträge Teil von Lehrveranstaltungsreihen der Universität Bremen und nicht frei zugänglich. Bei Interesse wird um Rücksprache mit dem Sekretariat unter sek-ric(at)dfki.de gebeten.

last updated 31.03.2023