Reach trucks feature a mast or fork carriage capable of moving forward and backward. In mast-reach trucks, the mast moves the forks forward beyond the front wheels to pick up or deposit loads, then retracts the forks and load during travel to keep the load's center of gravity within the support base; in fork-reach trucks, the carriage moves the forks forward beyond the front wheels for operations and retracts them within the support base during travel. Reach trucks are equipped with two forward-extending, elevated outriggers (legs) featuring wheels at their tips, which ensure stability when carrying a load. Unlike straddle-leg trucks, reach trucks have larger front wheels and higher outriggers that cannot slide underneath the load; instead, the mast-carrying the entire lifting mechanism-moves along rails inside the outriggers. This allows the forks to retract after a slight lift, ensuring operational stability. The mast can move forward along the inner rails of the outriggers to facilitate load handling. After picking up a load and lifting it slightly, the mast returns to its original position along the same rails, keeping the load's center of gravity within the vehicle's support footprint and ensuring excellent stability. They are well-suited for operations within workshops and warehouses.
The reach truck's mast, carrying the lifting mechanism, can move forward along rails inside the outriggers to facilitate load handling. After picking up a load and lifting it slightly, the mast returns to its original position along the inner rails.
With the advancement of artificial intelligence, the operating principle of modern intelligent reach trucks (forklift robots) has shifted from "automatic execution" based on pre-programming and fixed paths to "autonomous operation" characterized by capabilities such as environmental and task understanding, motion planning, and exception handling. The core approach employs a collaborative "cloud brain + on-site cerebellum" model to endow the forklift with autonomous perception, decision-making, and execution capabilities. This enables the machine to adapt to the existing site environment, thereby reducing the need for site modifications.
