Optimal Sensor Fusion for Autonomous Inland Shipping

Autonomous vessels for inland waterways will provide a solution to multitude of socio-economic problems. While the inland shipping sector suffers from an outflow of shippers and a lack of investment in new vessels resulting in the use of old-fashioned barge designs, a sustainable solution needs to be found for the ever increasing logistical transport sector e.g. Europe expects a 50% growth of cargo in EU ports by 2030. This outflow of labour and inflow of transportable goods, calls for a disruptive innovation like autonomous inland vessels, called autonomous barges. Autonomous shipping is an emerging field demonstrating the opportunities of translating mobile robotics sensor and software technologies employed in marine applications. Currently numerous sensors exist in a maritime environment. However proper reliability or adequacy is lacking especially regarding inland shipping applications. This PhD research tries to find an optimal sensor setup for the application of autonomous inland shipping and fusing the sensory information for accurate and efficient localization. The study focuses on the design and experimental validation of a sensor platform, based on GNSS and IMU, and fusing the sensory information enabling the determination of precise location of the vessel specifically for the Autonomous inland waterway applications.