CASE Construction Equipment is rolling out two new automation technologies, Click&Dig and Perception, for its wheel loaders to boost efficiency and safety.
At CNH’s CASE plant in Lecce, Italy, a group of young engineers is pursuing the long-term vision of fully autonomous construction machinery. Led by Advanced Electronics Manager Andrea Gravili, the team has achieved a major milestone this year with the launch of these two key automated features.
Click&Dig introduces three automated functions for wheel loaders — AutoDig, AutoDump, and AutoMetering — streamlining repetitive tasks. Meanwhile, Perception is an AI-powered system that uses cameras and sensors to detect workers, vehicles, and obstacles around the machine, enhancing safety and assisting operators in making better decisions.
According to Gravili, Perception was trained with artificial intelligence to identify common construction-site hazards ranging from rock piles to moving equipment and people. The system combines visual and radar input for greater reliability: “If the camera view is blocked by dust, the radar still picks up the obstacle,” he explains. Once a hazard is detected, the operator receives a brake alert.
Importantly, the initiative isn’t about replacing operators, says Antonio Venezia, CNH’s Director of Electronics for Construction Equipment. “While I may not spend full days in my car, operators spend entire shifts in these machines,” he notes. “Our role is to make their work easier, safer, and more comfortable — not to take their place.”
At CNH’s CASE plant in Lecce, Italy, a group of young engineers is pursuing the long-term vision of fully autonomous construction machinery. Led by Advanced Electronics Manager Andrea Gravili, the team has achieved a major milestone this year with the launch of these two key automated features.
Click&Dig introduces three automated functions for wheel loaders — AutoDig, AutoDump, and AutoMetering — streamlining repetitive tasks. Meanwhile, Perception is an AI-powered system that uses cameras and sensors to detect workers, vehicles, and obstacles around the machine, enhancing safety and assisting operators in making better decisions.
According to Gravili, Perception was trained with artificial intelligence to identify common construction-site hazards ranging from rock piles to moving equipment and people. The system combines visual and radar input for greater reliability: “If the camera view is blocked by dust, the radar still picks up the obstacle,” he explains. Once a hazard is detected, the operator receives a brake alert.
Importantly, the initiative isn’t about replacing operators, says Antonio Venezia, CNH’s Director of Electronics for Construction Equipment. “While I may not spend full days in my car, operators spend entire shifts in these machines,” he notes. “Our role is to make their work easier, safer, and more comfortable — not to take their place.”