Development of CAD codes for the job integration of industrial robots

IF 2.9 Q2 ROBOTICS

Robotics Pub Date : 1987-09-01 DOI:10.1016/0167-8493(87)90054-4

G.M. Acaccia, R.C. Michelini, R.M. Molfino

引用次数: 7

Abstract

The work of the Industrial Robot Design Research Group working at the University of Genoa, Italy, is summarized. The reasons for developing special-purpose CAD codes are noted, together with a discussion of the approach that has been utilized. An example procedure concerning the selection of the controlling strategies is presented, with typical output results. The integration of the robotic devices into manufacturing lines is discussed with an indication of the computational codes presently under development.

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工业机器人作业集成CAD代码的开发

对意大利热那亚大学工业机器人设计研究组的工作进行了总结。指出了开发专用CAD代码的原因，并讨论了所采用的方法。给出了控制策略选择的实例程序，并给出了典型的输出结果。讨论了机器人设备与生产线的集成，并指出了目前正在开发的计算代码。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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