The invention relates to the field of machine vision and artificial intelligence, in particular to a tire crane cart anti-collision method, device and system based on AI vision, and the method comprises the steps that driving information of a tire crane cart and environment image data around the tire crane cart are acquired; processing the environment image data by using a preset deep learning segmentation model to obtain an obstacle recognition result in the environment, the deep learning segmentation model comprising a plurality of detection heads for detecting targets of different sizes; performing continuous inter-frame tracking on an obstacle in the environment based on the obstacle recognition result to obtain movement information of the obstacle; judging whether a collision risk exists between the tire crane cart and the obstacle or not according to the driving information and the movement information; and when it is judged that the collision risk exists, corresponding anti-collision processing is carried out according to the collision risk. According to the invention, the anti-collision accuracy and reliability can be improved, and the safety of tire crane cart operation is improved.
本发明涉及机器视觉和人工智能领域,具体是一种基于AI视觉的轮胎吊大车防撞方法、设备及系统,所述方法包括:获取轮胎吊大车的行驶信息和所述轮胎吊大车周围的环境图像数据;利用预设的深度学习分割模型对所述环境图像数据进行处理,得到环境中的障碍物识别结果,所述深度学习分割模型包括检测不同尺寸目标的多个检测头;基于所述障碍物识别结果对环境中的障碍物进行连续帧间的跟踪,以获得所述障碍物的运动信息;根据所述行驶信息和所述运动信息判断所述轮胎吊大车与所述障碍物之间是否存在碰撞风险;当判断存在碰撞风险时,根据所述碰撞风险进行对应的防撞处理。本发明能够提高防撞的准确性和可靠性,提高轮胎吊大车作业的安全性。
Tire crane cart anti-collision method, equipment and system based on AI vision
一种基于AI视觉的轮胎吊大车防撞方法、设备及系统
03.09.2024
Patent
Elektronische Ressource
Chinesisch
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