Industrial robot autonomous assembly task planning method based on multi-agent large model

Abstract

The embodiment of the invention provides an industrial robot autonomous assembly task planning method based on a multi-agent large model, and belongs to the technical field of automatic assembly. The method comprises the steps of obtaining assembly task data of an assembly object, wherein the assembly task data comprises a task instruction for assembling the assembly object and an assembly manual; analyzing the task instruction and the assembly manual to obtain task execution logic; performing real-time acquisition on an assembly environment when the assembly object is assembled to obtain a target image; multi-modal sensing is conducted on the target image, a sensing result is obtained, and the sensing result comprises the position of at least one assembly of the assembly object in the assembly environment; and converting the task execution logic and the perception result into a planning domain definition language format, and performing assembly task planning through the behavior tree to obtain a target assembly task. According to the embodiment of the invention, the assembly efficiency and precision of the industrial robot are improved. 本申请实施例提供了一种基于多智能体大模型的工业机器人自主装配任务规划方法，属于自动化装配技术领域。该方法包括：获取装配对象的装配任务数据，装配任务数据包括对装配对象进行装配的任务指令和装配手册；对任务指令和装配手册进行解析，得到任务执行逻辑；对装配对象进行装配时的装配环境进行实时采集，得到目标图像；对目标图像进行多模态感知，得到感知结果，感知结果包括装配对象的至少一个组件在装配环境中的位置；将任务执行逻辑和感知结果转换为规划领域定义语言格式，并通过行为树进行装配任务规划，得到目标装配任务。本申请实施例提升了工业机器人的装配效率和精度。