Abstract
Cargo handling in ship operations poses risks due to heavy loads, necessitating innovation to mitigate accidents. Automation and remote control offers safer and more efficient operations by moving people from hazardous situations. Smaller and remote ports often rely on geared ships, which are typically manually operated. A first step towards automation is to remotely control these cranes. In remote control, the operator needs to gain situational awareness through sensor inputs. Previous research has shown that there is a need to investigate the sensor configuration and placement to provide situational awareness, particularly considering the placement of cargo onboard. This study seeks to identify needed sensor configurations for situational awareness in remote control of ship cranes using a simulator framework. A modular crane simulator framework has been developed to evaluate situational awareness for different sensor configurations. The sensor configuration has been evaluated with feedback from a crane expert. This research has identified potential sensor configurations for enhancing situational awareness in remote crane operations. The developed simulator framework has demonstrated its flexibility and efficiency as a platform for testing and optimizing cargo handling operations.
