For my Master’s thesis, I developed and trained an audio-based localization system for indoor localization called AudioLocNet. AudioLocNet is based on convolutional neural networks and maps recordings from a small(10cm diameter) microphone array to a grid of locations around said array. AudioLocNet was made to be used by swarms of small robots to locate each other using audio signals. AudioLocNet was trained using orthogonal chirp signals which have a low cross-correlation. Said signals can also be used for simultaneous communications between multiple robots. These signals were recorded in indoor environments ranging from simple line-of-sight environments to reverberant non-line-of-sight ones. Audio signals are used since they form a propagational middle class when compared to radio frequency (RF) and light-based signals for localization. Whereas light requires a line of sight, audio can bend around corners; and whereas RF signals pass through walls, reaching robots that are outside of each other’s spheres of influence, audio will not.
AudioLocNet reaches high accuracies for both a coarse grid (99.96 %) and a fine grid (99.89 %) of possible locations, where only the final layer of the network architecture must be changed to account for the increased resolution of the fine grid.

In order to make offshore working conditions safer, Ampelmann B.V. builds platforms that stay stable by compensating for a ship’s motion. These platforms are controlled via motion reference units (MRUs). In order to test the performances of these MRUs, a linear motion MRU test setup was developed. The system was divided into three parts: hardware, software and MRU assessment. This thesis focuses on the design and implementation of the MRU assessment part and on testing MRUs with the complete prototype setup.
Ampelmann supplied the MRU with which the test were conducted. Validation tests have been done with a simulator and with the setup itself. Included in the assessment of the MRUs was the latency, signal-tonoise ratio and low-frequency behaviour, compared to a ground truth. Concluded from the tests was that the designed test setup has potential to accurately assess the performance of MRUs. There are some minor improvements to be made, but the overall system works as intended.