机械加工中的工业机器人:视角与局限

IF 2.9 Q2 ROBOTICS
Robotics Pub Date : 2023-11-24 DOI:10.3390/robotics12060160
Mantas Makulavičius, S. Petkevičius, J. Rožėnė, Andrius Dzedzickis, V. Bučinskas
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引用次数: 0

摘要

最近,出现了使用软材料或超大尺寸部件进行生产的需求,这就需要使用工业机器人来提供负担得起的特殊解决方案。工业机器人在加工操作中具有灵活性、精确性和一致性,因此非常适合此类任务。然而,机器人的应用也面临着一些限制,如材料和工具种类繁多、对环境变化的适应性低、灵活性问题、复杂的工具路径准备过程以及质量控制方面的挑战。工业机器人技术的应用包括对金属、塑料和木材等各种材料进行切割、铣削、钻孔和打磨等工序。先进的机器人技术涉及机器人技术的最新进展,包括集成复杂的控制系统、传感器、数据融合技术和机器学习算法。这些创新技术使机器人能够更好地适应环境并与环境互动,最终提高机器人的精确度。本研究的主要重点是涵盖最常见的工业机器人加工过程,并确定特定的先进技术如何提高其性能。在大多数研究文献中,所有操作的主要研究目标都是增强机器人手臂结构的刚度。一些出版物提出了规划机器人姿势或工具方向的方法。与此相反,其他文献则侧重于通过利用先进的控制和计算(包括整合所收集传感器数据的机器学习方法)来优化加工参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Industrial Robots in Mechanical Machining: Perspectives and Limitations
Recently, the need to produce from soft materials or components in extra-large sizes has appeared, requiring special solutions that are affordable using industrial robots. Industrial robots are suitable for such tasks due to their flexibility, accuracy, and consistency in machining operations. However, robot implementation faces some limitations, such as a huge variety of materials and tools, low adaptability to environmental changes, flexibility issues, a complicated tool path preparation process, and challenges in quality control. Industrial robotics applications include cutting, milling, drilling, and grinding procedures on various materials, including metal, plastics, and wood. Advanced robotics technologies involve the latest advances in robotics, including integrating sophisticated control systems, sensors, data fusion techniques, and machine learning algorithms. These innovations enable robots to adapt better and interact with their environment, ultimately increasing their accuracy. The main focus of this study is to cover the most common industrial robotic machining processes and to identify how specific advanced technologies can improve their performance. In most of the studied literature, the primary research objective across all operations is to enhance the stiffness of the robotic arm’s structure. Some publications propose approaches for planning the robot’s posture or tool orientation. In contrast, others focus on optimizing machining parameters through the utilization of advanced control and computation, including machine learning methods with the integration of collected sensor data.
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来源期刊
Robotics
Robotics Mathematics-Control and Optimization
CiteScore
6.70
自引率
8.10%
发文量
114
审稿时长
11 weeks
期刊介绍: Robotics publishes original papers, technical reports, case studies, review papers and tutorials in all the aspects of robotics. Special Issues devoted to important topics in advanced robotics will be published from time to time. It particularly welcomes those emerging methodologies and techniques which bridge theoretical studies and applications and have significant potential for real-world applications. It provides a forum for information exchange between professionals, academicians and engineers who are working in the area of robotics, helping them to disseminate research findings and to learn from each other’s work. Suitable topics include, but are not limited to: -intelligent robotics, mechatronics, and biomimetics -novel and biologically-inspired robotics -modelling, identification and control of robotic systems -biomedical, rehabilitation and surgical robotics -exoskeletons, prosthetics and artificial organs -AI, neural networks and fuzzy logic in robotics -multimodality human-machine interaction -wireless sensor networks for robot navigation -multi-sensor data fusion and SLAM
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