【标题】Application of Automatic Recognition and Positioning Technology of Industrial Robot based on Monocular Vision Technology in Vehicle Manufacturing
【参考中译】基于单目视觉技术的工业机器人自动识别定位技术在汽车制造中的应用
【类型】 期刊
【关键词】 Monocular vision; Automatic identification; Positioning technology; Machine vision
【参考中译】 单目视觉;自动识别;定位技术;机器视觉
【作者】 Hongyu Chen
【摘要】 Combining machine vision technology with intelligent algorithms to improve the automatic identification and positioning technology of industrial robots to meet the production needs in different industrial environments is the current research direction of intelligent robots. In this study, an automatic identification and positioning technology for industrial robots based on monocular vision technology is proposed. First, the template matching algorithm and the Scale-invariant feature transform (SIFT) algorithm are introduced. Aiming at the shortcomings of the Hessian matrix in the SIFT algorithm in the process of eliminating boundary effects, an improved SIFT algorithm using Harris corner point detection is further proposed, and the improved SIFT algorithm is used in the automatic recognition and target positioning operations of industrial robots. In order to verify the performance of the proposed improved SIFT algorithm, the recognition accuracy and positioning angle deflection of the algorithm in different plastic sheets were detected. The experimental results show that under the improved SIFT algorithm, the recognition accuracy of five different styles of plastic sheets is above 98%. The improved SIFT algorithm also has less error between the predicted value and the actual value of the positioning angle deflection on the four plastic sheets. The robot under the improved algorithm is applied to the vehicle manufacturing industry and the production efficiency of the vehicle is improved through the automatic recognition and positioning technology of intelligent robot.
【参考中译】 将机器视觉技术与智能算法相结合，提高工业机器人的自动识别和定位技术，以满足不同工业环境下的生产需求，是当前智能机器人的研究方向。本文提出了一种基于单目视觉技术的工业机器人自动识别与定位技术。首先介绍了模板匹配算法和尺度不变特征变换(SIFT)算法。针对SIFT算法中海森矩阵在消除边界影响的过程中存在的不足，进一步提出了一种基于Harris角点检测的改进SIFT算法，并将其应用于工业机器人的自动识别和目标定位操作中。为了验证改进的SIFT算法的性能，测试了该算法在不同塑料板材上的识别精度和定位角度偏差。实验结果表明，在改进的SIFT算法下，对5种不同风格的塑料板材的识别准确率均在98%以上。改进的SIFT算法对四种塑料板材的定位角挠度的预测值与实际值之间的误差也较小。将改进算法下的机器人应用于汽车制造行业，通过智能机器人的自动识别和定位技术，提高了车辆的生产效率。
【来源】 International Journal of Vehicle Structures and Systems 2023, vol.15, no.3
【入库时间】 2024/5/31
【标题】Industrial Robots: Remote Monitoring and Control Solution Boosts Productivity
【参考中译】工业机器人：远程监控和控制解决方案提高生产力
【作者】 Ryan Cox
【摘要】 A human-centered remote monitoring and control system for industrial robots upgrades remote connectivity and control. It's a scenario many integrators are all too familiar with: A robot has failed in the middle of production, bringing an entire line to a halt. Every hour of downtime costs the client tens of thousands of dollars. You've been on several calls already, but you need to get onsite and the earliest you can make it is tomorrow morning. The fix itself-updating a waypoint-takes less than 10 min. The production manager is delighted that production is up and running again, but in the time it has taken to get onsite, the facility is down hundreds of thousands of dollars.
【参考中译】 以人为本的工业机器人远程监控系统升级了远程连接和控制。这是许多集成商都非常熟悉的场景：机器人在生产过程中发生故障，导致整条生产线停止。每一个小时的停机时间都会让客户损失数万美元。您已经打过几个电话了，但您需要赶到现场，最早也是明天早上。修复本身（更新航路点）只需不到10分钟。生产经理很高兴生产再次启动并运行，但在到达现场的时间内，该设施损失了数十万美元。
【来源】 Machine Design 2023, vol.95, no.6
【标题】Human-Robot Interaction in Social Robotics
【参考中译】社交机器人学中的人机交互
【作者】 Takayuki Kanda; Hiroshi Ishiguro
【摘要】 Published in 2013, this book explores human-robot interaction in the field of social robotics. It delves into numerous areas of human-robot interaction, such as communication, behavior, emotions, and social relationships. Kanda and Ishiguro examine the problems and prospects in building robots that can interact socially and meaningfully with people. They discuss robot appearance, gesture recognition, verbal and nonverbal communication, and the ethical implications of human-robot interactions.
【参考中译】 这本书出版于2013年，探讨了社交机器人领域的人机交互。它深入研究了人机交互的众多领域，例如沟通、行为、情感和社交关系。神田和石黑一雄研究了制造能够与人们进行社交和有意义互动的机器人的问题和前景。他们讨论了机器人外观、手势识别、言语和非言语交流以及人与机器人互动的道德含义。
【来源】 XRDS: Crossroads 2023, vol.30, no.1