2019 4th International Conference on Control and Robotics Engineering (ICCRE)最新文献_第2页

Adaptive Feed Control for Machining with Industrial Robots 工业机器人加工的自适应进给控制

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724141

L. Lienenlüke, S. Wurm, S. Storms, C. Brecher

{"title":"Adaptive Feed Control for Machining with Industrial Robots","authors":"L. Lienenlüke, S. Wurm, S. Storms, C. Brecher","doi":"10.1109/ICCRE.2019.8724141","DOIUrl":"https://doi.org/10.1109/ICCRE.2019.8724141","url":null,"abstract":"The sector of machining hard materials like aluminium, steel or nickel-base alloys is dominated by conventional machine tools because they provide high reliability in production time and process accuracy. However, processing soft materials or products with low quality requirements are getting more interesting for standard industrial robots because of their low investment risks and short delivery periods. On the other hand, disadvantages like low absolute accuracy and low structural stiffness limit the area of industrial applications. Current research activities are focusing on compensation algorithms to reduce the static offset induced by process forces. Thus, this paper presents an approach of a control system which adapts automatically the feed rate depending on the cutting scenario. Linked with a Computer-Aided-Manufacturing system, predefined machining data is analyzed and stored on a separate Edge-Device. This Edge-Device communicates with the machining spindle and monitors the spindle power to monitor the cutting scenario. On this basis, deviations of the milling tool in the areas of entering and leaving the material could be reduced.","PeriodicalId":366332,"journal":{"name":"2019 4th International Conference on Control and Robotics Engineering (ICCRE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127954869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Design and Research of Lower Limb Walking-assisted Exoskeleton Robot 下肢行走辅助外骨骼机器人的设计与研究

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724151

Qing Li, Yuxi Feng, Weipeng Zhang, Rongshuai Liu

引用次数: 5

Compensation of Process Forces with a Model-Based Feed-Forward Control for Robot Machining 基于模型前馈控制的机器人加工力补偿

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724312

L. Gründel, L. Lienenlüke, S. Storms, C. Brecher

引用次数: 4

Plane Motion and Structure from Two Separate Ellipse Correspondences under 2D Homography 二维单应性下两个独立椭圆对应的平面运动和结构

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724150

Yang Guo

引用次数: 0

An Action Generator for Small Humanoid Robot based on Inverse Kinematics 基于逆运动学的小型人形机器人动作生成器

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724360

Chuande Liu, Ruiming Qian

引用次数: 0

The Design and Implementation of GPS Controlled Environment Monitoring Robotic System based on IoT and ARM 基于物联网和ARM的GPS控制环境监测机器人系统的设计与实现

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724268

Hasan Salman, Md Sezadur Rahman, Md Abu Yousuf Tarek, Jun Wang

{"title":"The Design and Implementation of GPS Controlled Environment Monitoring Robotic System based on IoT and ARM","authors":"Hasan Salman, Md Sezadur Rahman, Md Abu Yousuf Tarek, Jun Wang","doi":"10.1109/ICCRE.2019.8724268","DOIUrl":"https://doi.org/10.1109/ICCRE.2019.8724268","url":null,"abstract":"Environmental monitoring systems are often designed to measure and log the current status of an environment or to establish trends in environmental parameters. In this paper, We proposed an autonomous robotic system that is designed and implemented to monitor environmental parameters such as temperature, humidity, air quality, and harmful gas concentration. The robot has GPS coordinates, and it can store data on the ThingSpeak IoT platform. The mobile robot is controlled by a smartphone which runs an app built on the Android platform. The whole system is realized using a cost-effective ARM-based embedded system called Arduino and Raspberry Pi which communicates through a wireless network to the IoT platform, where data are stored, processed and can be accessed using a computer or any smart device from anywhere. The system can update sensor data to IoT server every 15 seconds. The stored data can be used for further analysis of the reduction of pollution, save energy and provide an overall living environment enhancement. The robotic system has designed for cost-effective remote monitoring environmental parameters without any human intervention to avoid health risk efficiently. A proof-of-concept prototype has been developed to illustrate the effectiveness of the proposed system.","PeriodicalId":366332,"journal":{"name":"2019 4th International Conference on Control and Robotics Engineering (ICCRE)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127659402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Terminal Motion Control of Multicopter Group 多旋翼机群终端运动控制

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724373

V. Pshikhopov, M. Medvedev, T. Medvedeva

引用次数: 1

Hybrid Binary Bat Algorithm with Cross-Entropy Method for Feature Selection 特征选择的交叉熵混合二进制Bat算法

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724270

Guocheng Li, Chengyi Le

引用次数: 7

An Intelligent Method for Prediction of Surface-Hardness in Surface-Hardened Steel Rod 表面淬火钢棒表面硬度的智能预测方法

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724238

Zhongyang Zhu, Guangmin Sun, C. He, Anqi Liu

{"title":"An Intelligent Method for Prediction of Surface-Hardness in Surface-Hardened Steel Rod","authors":"Zhongyang Zhu, Guangmin Sun, C. He, Anqi Liu","doi":"10.1109/ICCRE.2019.8724238","DOIUrl":"https://doi.org/10.1109/ICCRE.2019.8724238","url":null,"abstract":"Surface-hardened steels are widely used in many industrial components, such as cam and gears. Surface-hardness (SH) prediction plays an important role in assessing the quality of the surface-hardened steel. In this paper, an intelligent method for automatic SH prediction model establishment is proposed. The proposed intelligent approach involves three key steps. Firstly, hysteresis loops (HLs) are measured from the prepared surface-hardened steel rods with different SHs by a sensor. Secondly, a binary particle swarm optimization (BPSO) feature selection is applied to automatically select optimal feature subset from the measured HLs signal. Finally, a single-layer feedforward neural network (FNN) model is utilized to bridge the relationship between the selected features and SH. The experimental results show that the intelligent method can automatically establish SH prediction model. The optimal feature subset based single-layer FNN model can accurately predict SHs in surface-hardened steel rods with a prediction error of 0.298 %, indicating that the intelligent method can be integrated in an industrial robot for SH prediction in surface-hardened steel rod.","PeriodicalId":366332,"journal":{"name":"2019 4th International Conference on Control and Robotics Engineering (ICCRE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121403261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Gait Recognition and Robust Autonomous Location Method of Exoskeleton Robot Based on Machine Learning 基于机器学习的外骨骼机器人步态识别与鲁棒自主定位方法

2019 4th International Conference on Control and Robotics Engineering (ICCRE) Pub Date : 2019-04-01 DOI: 10.1109/ICCRE.2019.8724217

Cuihong Gu, Minghan Gao, Weixing Qian, Qingyu Deng, Tianyu Cheng, Siliang Chen

{"title":"Gait Recognition and Robust Autonomous Location Method of Exoskeleton Robot Based on Machine Learning","authors":"Cuihong Gu, Minghan Gao, Weixing Qian, Qingyu Deng, Tianyu Cheng, Siliang Chen","doi":"10.1109/ICCRE.2019.8724217","DOIUrl":"https://doi.org/10.1109/ICCRE.2019.8724217","url":null,"abstract":"Focusing on the autonomous location method of lower extremity exoskeleton robot in complex environment, this paper presents a gait type recognition method based on support vector machine (SVM)C and an autonomous location method based on inertial information mapping model and system reconstruction. In this paper, support vector machine is used to effectively recognize various kinds of conventional gait types of exoskeleton robots. The inertial information mapping models among different parts of the lower limbs of the robots under different gaits are established respectively. Aiming at the problem of the failure of the inertial measurement unit at the end of the limb in the impact or high overload motion, a robust autonomous location method based on system reconstruction is studied. The experiment results show that, using different neural network model parameters under different gaits can be used to reduce the complexity of the network model. While the inertial measurement unit at the end of the limb fails, the location performance of the exoskeleton robot navigation system based on this method, is equal to that of the inertial navigation system at the end of the limb with same sensor precision.","PeriodicalId":366332,"journal":{"name":"2019 4th International Conference on Control and Robotics Engineering (ICCRE)","volume":"47 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114030639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1