工业机器人用超声波测距和成像系统

IF 2.9 Q2 ROBOTICS

Robotics Pub Date : 1987-06-01 DOI:10.1016/0167-8493(87)90006-4

J. Knight, S. Pomeroy, H. Dixon, M. Wybrow

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引用次数: 9

摘要

综述了工业机器人超声传感器系统的发展与实现。介绍了诺丁汉大学在传感器、测距和成像方面的研究进展。测距系统具有独特的操作规范，可以在足够的分辨率下进行远距离测量，并在较近的距离上进行极精细的分辨率测量。对成像的初步评估表明，200kHz的工作频率在系统分辨率和声能吸收之间给出了一个公平的折衷。

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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Ultrasonic distance measuring and imaging systems for industrial robots

The development and implementation of Ultrasonic Sensor Systems for Industrial Robots is reviewed. The research developments concerning transducers, ranging and imaging at the University of Nottingham are presented. The ranging system possess a unique operating specification which allows long range measurement at adequate resolution and extremely fine resolution at closer distances. Initial evaluations of imaging suggest that an operating frequency of 200kHz gives a fair compromise between system resolution and absorption of sound energy.

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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