Dynamic Crane Workspace Update for Collision Avoidance During Blind Lift Operations

Abstract

Cranes are associated with high levels of accidents and struck-by fatalities in many industrial settings. This is due to the congested nature of crane operation sites and the high cognitive load for the crane operator to track the load position throughout the lifting operation, especially during blind lifts. Current research on crane safety assistance systems focuses on preventing collisions with static entities such as existing building structures but do not adequately handle dynamic entities such as workers and movable containers. This research proposes a dynamic crane workspace updating method for collision avoidance during blind lift operations. The position and orientation of the crane load, as well as the position and orientation of surrounding obstacles, are automatically tracked and updated in a 3D crane workspace model during lifting operations. The load base position is first estimated using forward kinematics obtained from an encoder system. Then the load swing and load rotation are corrected for using a vision-based load detection algorithm. A static map of surrounding obstacles is initially obtained using 3D laser scanning. The map is then updated over the course of a lifting operation through semi-automated obstacle placement. In addition, a vision-based worker detection algorithm is used to track the position of workers in proximity to the load. Finally, the crane workspace is updated in real-time for the crane operator through a 3D user interface and warnings are issued whenever a potential collision scenario is detected. The proposed method was evaluated at a crane yard where multiple blind lift scenarios were carried out. Experimental results indicate that the proposed method can potentially improve the situational awareness of the crane operator for blind lift operations.