In collaboration with the National Science Foundation, equipment manufacturers and several research universities, Manitowoc Cranes will work to create a new cyber-physical operation system aimed at increasing safety for workers at construction sites. Manitowoc’s role in the project is to provide researchers with industry expertise and to seek out and implement practical applications for the researchers’ findings.
Lynn Dietrich, director of engineering at Manitowoc states, “We’ve taken on this collaboration with a great sense of responsibility and conviction. By using advances in technology and computing, we should be able to make significant steps in improving the efficient use of cranes on job sites.”
The four-year project will begin January 2016 and seeks to blend advances in robotics, computer-aided vision and construction management techniques with the goal of generating tools to aid in the planning and monitoring of crane systems. The idea being tested is that cranes can be successfully monitored and controlled using computer programming, advanced robotics and 3-D cameras to discern distances between objects and the crane and to predict and avoid collisions. Additionally, the data gathered using computer-assisted monitoring of the crane’s environment will be used for simulating and planning future construction sites.
The successful implementation of the proposed tools will give crane operators the ability to respond to computer-generated feedback concerning the crane’s stability, structural overload, and the potential for collision with other objects on the construction site, thereby increasing worker safety.
The collaborative project will also look at methods to
- Use computer simulations to anticipate construction site hazards during the planning phase.
- Analyze equipment use and seek ways to improve efficiency.
- Monitor equipment in use surrounding cranes and anticipate safety issues.
- Analyze the efficient placement of dynamic resources.
- Provide real-time feedback to crane operators regarding stability.
- Improve the crane operator’s environment, or cockpit, to include visual and haptic cues.
- Predict real time job site hazards using computer models and 3-D object recognition.