ForschungBig Data und Machine Learning
Robust visual navigation for autonomous underwater track vehicles

Robust visual navigation for autonomous underwater track vehicles

Leitung:  Brenner, Kirchner
Team:  Lewin Probst
Jahr:  2015
Laufzeit:  2015
Ist abgeschlossen:  ja

Underwater track vehicles, also known as crawler, are universal carrier platforms for many different applications. Crawler having an autonomous navigation would enable the possibility of executing long-term observations without a connection to a base station. This thesis presents approaches that use previous knowledge about the scene that is integrated into motion estimation step by replacing RANSAC with PROSAC to make the motion estimation more robust. Running into degeneration may happen although a robust outlier removal scheme is being used, the thesis additionally presents a strategy to prevent running into degeneration as well as strategy for the recovering from a degeneration using a snapshot procedure