A framework for real-time pro-active safety assistance for mobile crane lifting operations

Despite many safety considerations addressed in lift pre-planning, the ability to provide real-time safety assistance to crane operators and to mitigate human errors during the lifting operation is missing. This research developed a framework for real-time pro-active safety assistance for mobile crane lifting operations. First, crane poses are reconstructed in real-time based on the critical motions of crane parts captured by a sensor system. Second, as-is lift site conditions are automatically modeled and updated based on point cloud data. Lastly, the risk of colliding the crane parts and lifted load into nearby obstructions is pro-actively analyzed and warnings are provided to the operator through a graphical user interface. A prototype system was developed based on the framework and deployed on a mobile crane. Field test results indicate that the system can accurately reconstruct crane motion in real-time and provide pro-active warnings that allow the operator to make timely decisions to mitigate the risk. [Display omitted] •Spatial conflicts and operator errors are major causes in crane related accidents.•A framework for real-time safety assistance for mobile cranes is proposed.•A prototype system has been developed and its implementation described.•Field validation indicates a potential for improving overall crane safety.