In this paper, we propose an end-to-end automatic walking system for construction machinery, which uses binocular cameras to capture images of construction machinery for environmental perception, detects target information in binocular images, estimates the relative distance between the current target and cameras, and predicts the real-time control signal of construction machinery. This system consists of two parts: the binocular recognition ranging model and the control model. Objects within 5 m can be quickly detected by the recognition ranging model, and at the same time, the distance of the object can be accurately ranged to ensure the full perception of the surrounding environment of the construction machinery. The distance information of the object, the feature information of the binocular image, and the control signal of the previous stage are sent to the control model; then, the prediction of the control signal of the construction machinery can be output in the next stage. In this way, the automatic walking experiment of the construction machinery in a specific scenario is completed, which proves that the model can control the machinery to complete the walking task smoothly and safely.
Keywords: binocular detection; construction machinery; end-to-end; ranging; unmanned driving.