Anti-collision during Truck Crane Lifting Based on Virtual Wall

Abstract

To reduce collision accident occurred between the boom of truck crane and obstacles in work area during lifting operations. Based on obstacle classification model, the shape and location data of obstacles are collected accurately by adopting self-exploration way for boom head of crane. By establishing cylinder coordinate system of crane, the work area is divided into many sectors according to crane slewing angle, and then the sectors are divided into many fan grids based on the distance to the rotation center. Since obstacle data are stored precisely in the fan grids, the three-dimensional virtual walls of safe lifting operations are built by using these fan grids' data. The next boom's movement and position are predicted by the weighted linear regression model by using last 20 boom position data. Based on boom's movement trend and different distances to the virtual wall, the different boom control strategies of non-intervention, deceleration, micro-movement and prohibition are utilized. The function testing of actual operating environment demonstrate that the system could effectively prevent the collisions between the boom and obstacles of work area.