Modern tower cranes can reach a height of more than 200 meters. They operate in a complicated, chaotic and constantly changing environment. This creates obstacles for the crane operator: poor visibility and dead angles — places the operator can’t see.
Aiming to solve the problem is the Augmented Crane Navigation System (ACNS) project, which provides innovative intelligent operation of tower cranes on construction sites through the integration of highly accurate navigation receivers and a powerful processor unit.
Polish researcher Piotr Krystek took home the DLR Special Prize from the European Satellite Navigation Competition (ESNC) for the ACNS, which is designed to increase efficiency and safety at construction sites.
Using the ACNS, the position of the crane elements can be determined and oriented using four to five low-cost yet highly precise Galileo or GNSS receivers. The central processor calculates the best possible route for load management. In addition to the position values of the various satellite navigation receivers, the digital model of the physical structure or Building Information Model (BIM) is used. Using a head-up display, the visualization is projected directly onto the crane operator’s field of view to enable easy and precise navigation.
The ACNS has a modular design and can be mounted on the crane easily; this includes the retrofitting of existing cranes.
The project is still in the concept phase. To implement the idea, the market must be explored and feasibility studies carried out with cranes in collaboration with crane manufacturers, Krystek said.
The ACNS also could be transferred to other construction machinery and commercial vehicles, Krystek said. As one of the leading economic sectors, the construction industry can benefit immensely from GNSS-based solutions.
Krystek was inspired to pursue the project because of the tower cranes visible from his window in Krakow — along with the availability of low-cost RTK receivers. He is also inspired by the trend to automate everything that can be automated, such as self-driving cars.