Third party funded individual grant
Acronym: AC
Start date : 01.07.2017
End date : 30.06.2020
Autonomous applied logistics, especially in context of Industry 4.0, is an important factor for fully automated systems. These systems involve autonomous operation of loading and unloading processes, safety measures by detecting persons in danger zones and the general optimization of the logistical processes.
Especially, the application of these systems in a harbor environment, where different systems from all over the world interact, increases the complexity of the loading and unloading processes. The aim of this research project is to determine the feasibility of automating the unloading process by segmenting, classifying and fitting laser range data by using Machine Learning techniques.
Autonomous applied logistics, especially in context of Industry 4.0, is an important factor for fully automated systems. These systems involve autonomous operation of loading and unloading processes, safety measures by detecting persons in danger zones and the general optimization of the logistical processes.
Especially, the application of these systems in a harbor environment, where different systems from all over the world interact, increases the complexity of the loading and unloading processes. The aim of this research project is to determine the feasibility of automating the unloading process by segmenting, classifying and fitting laser range data by using Machine Learning techniques.