On the consistency of path smoothing and trajectory planning in CNC machining: A surface-centric evaluation

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Robotics and Computer-integrated Manufacturing Pub Date : 2024-09-23 DOI:10.1016/j.rcim.2024.102873
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Abstract

Path smoothing and trajectory planning are universally applied in computer-numerical-control (CNC) machining to avoid natural discontinuity of tangency and curvature at the junctions of G01 blocks. However, most existing methods primarily focus on path-centric indicators that consider the toolpath as a continuous curve, such as contour error and manufacturing efficiency, neglecting the global machining quality and failing to avoid surface inconsistencies, such as single tool marks. This paper establishes a theoretical framework to evaluate the global continuity of toolpaths and trajectories, proposing the consistency as a surface-centric evaluation that considers toolpaths as a surface in CNC machining. In this paper, the consistency is defined as similarity between adjacent toolpaths and trajectories when facing similar input fold-paths in single-point milling. The consistency of four typical existing methods representing a broad category of typical approaches is investigated based on the developed theory. As a theoretically ideal objective, the proposed strong consistency requires a path smoothing method robust to any positional disturbance on the input fold-paths, and this paper points out that few algorithms have achieved strong consistency so far. The proposed weak consistency focusing on the tangential disturbance is practical in the industry. Filtering-based methods without contour error limitations are proved to achieve weak consistency, and smoothing methods with explicit geometric constraints fail to achieve weak consistency. To facilitate evaluation on the consistency of more complex methods, this paper proposes numerical benchmarks and quantitative indicators which can determine whether a method is consistent by numerical experiments. Conducted on a 3-axis machine tool with a ball-end milling cutter, real-world experiments show that inconsistencies in toolpaths’ position and trajectories’ feedrate causes surface inconsistencies like single tool marks. The proposed consistency theory and the carefully designed benchmarks can serve as a novel evaluation for path smoothing and trajectory planning from a global perspective, and it can help to identify areas where inconsistencies may occur in single-point milling.
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论数控加工中路径平滑和轨迹规划的一致性:以表面为中心的评估
路径平滑和轨迹规划普遍应用于计算机数控(CNC)加工中,以避免 G01 块交界处切线和曲率的自然不连续性。然而,大多数现有方法主要关注以路径为中心的指标,将刀具路径视为连续曲线,如轮廓误差和制造效率,而忽视了全局加工质量,无法避免单刀痕等表面不一致性。本文建立了一个评估刀具路径和轨迹全局连续性的理论框架,提出一致性是一种以表面为中心的评估方法,将刀具路径视为数控加工中的一个表面。本文将一致性定义为在单点铣削中面对相似的输入折线路径时,相邻刀具路径和轨迹之间的相似性。基于所建立的理论,研究了代表一大类典型方法的四种现有典型方法的一致性。作为理论上的理想目标,所提出的强一致性要求路径平滑方法对输入折叠路径上的任何位置干扰都具有鲁棒性,本文指出,迄今为止很少有算法实现了强一致性。本文提出的弱一致性侧重于切向干扰,在行业中是实用的。事实证明,没有轮廓误差限制的基于滤波的方法可以实现弱一致性,而具有明确几何约束的平滑方法则无法实现弱一致性。为了便于评估更复杂方法的一致性,本文提出了数值基准和量化指标,通过数值实验来确定方法是否具有一致性。在使用球头铣刀的三轴机床上进行的实际实验表明,刀具路径位置和轨迹进给速度的不一致性会导致单刀痕等表面不一致性。提出的一致性理论和精心设计的基准可以从全局角度对路径平滑和轨迹规划进行新的评估,并有助于识别单点铣削中可能出现不一致的区域。
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来源期刊
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
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.
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