The invention discloses a tower crane real-time path planning system and method based on deep learning, and the system comprises a construction site environment real-time sensing module which is used for carrying out the real-time collection and processing of the space information of an object in a construction site environment, constructing a real-time construction site space model, and carrying out the real-time three-dimensional collision prediction based on the model; the tower crane data acquisition module is used for acquiring the operation action of a tower crane driver and the motion state of the tower crane and recording according to time to form a tower crane driver operation sequence and a tower crane motion state sequence; the real-time path planning module is used for training a neural network of a deep learning algorithm and learning real planning characteristics of a tower crane driver on a hanging object path; and meanwhile, the planned path is dynamically adjusted in real time, so that obstacles dynamically appearing on the construction site are avoided. According to the method, the overall rationality of path planning is ensured, the path planning is updated in real time according to the real-time information of the working scene of the tower crane, and interference caused by newly appearing obstacles in the operation process is avoided.
本发明公开了一种基于深度学习的塔机实时路径规划系统及方法,该系统包括:施工现场环境实时感知模块,用于对施工现场环境中物体的空间信息,进行实时采集处理,构建实时的施工现场空间模型,基于该模型,进行实时的三维碰撞预测;塔机数据采集模块,用于采集塔机司机的操作动作及塔机运动状态,按照时间记录,形成塔机司机操作序列及塔机运动状态序列;实时路径规划模块,对深度学习算法的神经网络进行训练,学习真实的塔机司机对吊物路径的规划特性;同时对规划路径进行实时动态调整,以规避施工现场动态出现的障碍物。本发明保证了路径规划的整体合理性,根据塔机工作场景的实时信息实时更新路径规划,避免运行过程中新出现障碍物带来的干扰。
Deep learning-based tower crane real-time path planning system and method
一种基于深度学习的塔机实时路径规划系统及方法
25.07.2023
Patent
Elektronische Ressource
Chinesisch
IPC: | B66C Krane , CRANES |
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