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焊接机器人智能控制程序的研究与实现

Intelligent Control System of Trajectory Planning for a Welding Robot

【作者】 迟宁

【导师】 王月海;

【作者基本信息】 北方工业大学 , 计算机应用技术, 2011, 硕士

【摘要】 焊接机器人机械臂的轨迹规划在工业机器人的智能控制中具有重要的地位。传统的机械臂焊接方法采用的是示教-再现方式,一次示教,整个工作流程都遵循示教的流程进行焊接,这种一成不变的焊接模式难以达到工业领域高效率、低耗能的要求,而通过人工优化焊接轨迹又存在优化困难并难于实现自动控制。因此,让焊接机器人机械臂在反复执行相同任务的过程中,通过智能算法,寻求一条效率更高、代价更低,乃至最优的轨迹规划成为焊接机器人领域智能控制的研究重点。本论文通过系统能量和时间优化两个方面,对机械臂焊接芯片的路径进行优化。系统能量方面,应用Denavit-Hartenberg理论进行关节坐标和笛卡尔坐标的转换,建立运动方程,通过设置满足工业需求的规则有效地实现机械手轨迹规划自学习的能力;时间优化方面,研究芯片焊点的分布,把问题转换成哈密尔顿回路求解问题,应用改进的遗传算法求得优化的哈密尔顿回路,使机械臂焊接路径得到优化,实验结果表明了改进的遗传算法在机械手焊接芯片实际应用的有效性。

【Abstract】 Welding robot manipulator trajectory planning for industrial robots intelligent control has an important position.The trajectory planning of welding robot manipulator occupy an important position in the intelligent control of industrial robots.The traditional method used by welding manipulator is teaching-reproduction, once teached, the entire workflow process will follow it to weld, while such static model hardly achieve the high efficiency, low power requirements of industrial welding, on the other hand, manual optimization of welding trajectory is very difficult and hard to get this under automatic control. For this reason, in the process of welding robot manipulator repeatedly perform the same tasks, how to find a more efficient, less costly, and even the optimal trajectory through smart algorithms is the key point in the field of intelligent control of welding robot.In this thesis, the chip welding trajectory of manipulator was optimised from both the system energy and time. In the aspect of system energy, the Denavit-Hartenberg theory was used to achieve joint coordinates and Cartesian coordinate transformation, establish the motion equations, so to obtain effective self-learning capabilities of welding robot manipulator trajectory planning by setting some rules to meet the industry needs. In the aspect of time optimization, through the research of chip solder joints’ distribution, the problem was transformed to the Hamilton circuit problem, improved genetic algorithm was used to obtaind optimal Hamilton circuit, so to optimise manipulator’s welding trajectory. The effectiveness of improved genetic algorithm in the practical application of manipulator’s chip welding was proved by the result of experiments.

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