Pengfei Su , Wei Wang , Kaiyuan Liu , Jin Zhang , Yantao He , Zhimin Wang , Lianyu Zheng
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引用次数: 0
Abstract
Robotic machining could provide a solution for removing supports from metal additive manufactured workpieces, replacing labor-intensive work. However, the robot’s intrinsic weaknesses of low positioning accuracy and structural rigidity primarily restrict its applications. Improving the accuracy of robotic machining remains an unresolved issue. A mixed solution is proposed, in which a portable CNC machine with the capability of visual feature recognition is equipped with a universal industrial robot. The robot implements positioning motions in a large space, while the portable CNC fulfills accurate machining motions on a local feature of the workpiece. A sizeable weight of the portable CNC exerts a moderate load on the industrial robot’s joints, increasing joint stiffness. The mixed machining system exhibits high accuracy and stiffness when milling a steel/titanium alloy workpiece, achieving tolerances up to ±0.04 mm on a 60×80 mm U-shaped path without exciting any structural vibration modes. When the dimension of the workpiece exceeds the machining range of the portable CNC, a combined algorithm of coarse-fine registration based visual identification and robot error compensation is designed to align the spatial coordinates of the machining motion with that of the positioning motion, thereby extending the machining range with high accuracy. Through the proposed mixed robot machining method, experiments of doubling the machining range have been done to verify that the mixed machining robotic system is able to slot a 550 mm-long path with accuracy of ±0.1 mm. Furthermore, the mixed robotic machining system is applied to recognize and remove multiple supports of lattices, grids and ribs from a titanium-alloy additive manufactured thin-wall workpiece with high accuracy and high efficiency.
机器人加工可为金属添加剂制造的工件去除支撑物提供解决方案,从而取代劳动密集型工作。然而,机器人定位精度低和结构刚性差的固有弱点主要限制了其应用。提高机器人加工的精度仍是一个悬而未决的问题。本文提出了一种混合解决方案,即在具有视觉特征识别功能的便携式数控机床上配备一个通用工业机器人。机器人在大空间内执行定位动作,而便携式数控机床则对工件的局部特征执行精确的加工动作。便携式数控系统的重量较大,会对工业机器人的关节造成一定的负荷,从而增加关节的刚度。在铣削钢/钛合金工件时,混合加工系统表现出很高的精度和刚度,在 60×80 mm 的 U 形路径上实现了高达 ±0.04 mm 的公差,且不会产生任何结构振动模式。当工件尺寸超出便携式数控系统的加工范围时,设计了一种基于视觉识别和机器人误差补偿的粗-细注册组合算法,使加工运动的空间坐标与定位运动的空间坐标保持一致,从而高精度地扩展了加工范围。通过所提出的混合机器人加工方法,进行了加工范围扩大一倍的实验,验证了混合加工机器人系统能够在 550 毫米长的路径上开槽,精度为 ±0.1 毫米。此外,混合机器人加工系统还能高精度、高效率地识别和去除钛合金增材制造薄壁工件上的多个支撑网格、栅格和肋条。
期刊介绍:
The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.