3D machine visual forklift travelling auxiliary safety system and method

Abstract

The invention discloses a 3D machine visual forklift travelling auxiliary safety system and method. The travelling state and peripheral operating environment of a forklift can be monitored in real time, and safety of personnel and assets in the forklift operation process is ensured. The system comprises an operating environment perceiving subsystem (1) formed by adopting a plurality of intelligent depth cameras as mains, a vehicle state monitoring subsystem (2) for collecting travelling states such as the speed, the posture and cornering of a vehicle, an output subsystem (3) for being connected with a vehicle power control assembly and controlling a braking control assembly, and an information processing subsystem (4) for logic control and intelligent judgment and recognition. According to the 3D machine visual forklift travelling auxiliary safety system and method, through the intelligent depth cameras and a plurality of sensors, the operating environment and the vehicle condition of the forklift are subjected to overall monitoring, obstacle detecting and warning can be provided, and through accurate recognition of personnel and objects, the functions of active personnel safety warning and controlling can be further achieved.

Description

technical field [0001] The invention relates to the technical field of 3D machine vision and intelligent safety assisted driving, in particular to a 3D machine vision forklift driving auxiliary safety system and method based on the fusion of an intelligent depth camera and multiple sensors. Background technique [0002] In modern large-scale industrial production and assembly plants and logistics warehousing, forklifts are an indispensable tool. When the forklift is moving the goods, the forklift driver's sight is easily blocked by the goods, which will cause safety hazards. Therefore, a forklift driving auxiliary safety system is needed to reduce or even avoid the occurrence of safety accidents. Most of the traditional safety driving assistance systems are based on ultrasonic, radar, infrared, laser and other point distance measurements to judge the surrounding conditions of the forklift, and the detection accuracy, resolution and recognition reliability are poor; the safet...

AI Technical Summary

Problems solved by technology

When the forklift is moving the goods, the forklift driver's sight is easily blocked by the goods, which will cause safety hazards. Therefore, a forklift driving auxiliary safety system is needed to reduce or even avoid the occurrence of safety accidents.

Most of the traditional safety driving assistance systems are based on ultrasonic, radar, infrared, laser and other point distance measurements to judge the surrounding conditions of the forklift, and the detection accuracy, resolution and recognition reliability are poor; the safety driving assistance systems based on machine vision mainly use grayscale Visually process and analyze the two-dimensional images of cameras or color cameras, and then make judgments. There are problems of high detection complexity, easy background interference, and poor recognition accuracy; multi-eye stereo vision based on multi-camera two-dimensional image synthesis There are problems of high calculation difficulty and poor detection stability in complex environments

[0003] Due to the complex factory environment where forklifts operate and the changing operating conditions of forklifts, traditional driving assistance safety systems have certain limitations. Most of them are only used as early warning reminders and cannot reliably guarantee the safety of forklift operations.

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