2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)最新文献_第2页

Vision System for Detecting and Locating Micro-Scale Objects with Guided Cartesian Robot 基于导向笛卡尔机器人的微尺度目标检测与定位视觉系统

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/ACIRS58671.2023.10240777

Naritpon Chavitranuruk, E. Pengwang

{"title":"Vision System for Detecting and Locating Micro-Scale Objects with Guided Cartesian Robot","authors":"Naritpon Chavitranuruk, E. Pengwang","doi":"10.1109/ACIRS58671.2023.10240777","DOIUrl":"https://doi.org/10.1109/ACIRS58671.2023.10240777","url":null,"abstract":"This paper aims to use a vision system to detect and locate the position of microscale workpiece on the GelPak & wafer ring and command the end-effector to move to the targeted positions by using 2 sets of cameras. The object that is investigated in this design is Chip On-Sub-mount Assembly (COSA) with a footprint of ${270}times {270}$ micrometers. The first camera is used to find the COSA's position and count the quantity of the COSA on the GelPak and wafer ring. The second camera is used to find the exact position of the COSA and then the end-effector is moved to the target position on COSA's sub-mount. The challenges in this process are accuracy, system integration, and the compliance of the GelPak and the wafer ring. With this proposed design, the performances of the system are examined and validated for the working prototype. The result of the wide camera for finding the approximate center position of the COSAs is 94% successful, the percentage of counting COSA is 90% accuracy. The XY position error from the given position compared to the center position of COSA's sub-mount is ${4}.{882} {mu} {m}$ and ${8}.{206} {mu}{m}$ for x and y axis respectively.","PeriodicalId":148401,"journal":{"name":"2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133684456","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: 0

Threshold-Based Electroencephalography Brain-Computer Interface for Robot Arm Control 基于阈值的脑电图脑机接口的机器人手臂控制

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/ACIRS58671.2023.10240250

M. Rusydi, Elita Amrina, Yoan Winata, Salisa Asyarina Ramadhani, R. Nofendra

{"title":"Threshold-Based Electroencephalography Brain-Computer Interface for Robot Arm Control","authors":"M. Rusydi, Elita Amrina, Yoan Winata, Salisa Asyarina Ramadhani, R. Nofendra","doi":"10.1109/ACIRS58671.2023.10240250","DOIUrl":"https://doi.org/10.1109/ACIRS58671.2023.10240250","url":null,"abstract":"Brain-Computer Interface (BCI) is a technique that uses real-time brain impulses to connect with and control external devices. BCI provides a new method for controlling external devices by translating brain signals into computer commands, facilitating the daily lives of people with disabilities and enhancing their ability to exhibit expected behavior. A Brain-Computer Interface (BCI) system based on Electroencephalography (EEG) was built to control the robotic arm. The EEG signals utilized included both eyes blinking, the right eye, the left eye, and the jaw contraction. EEG data were recorded from seven healthy subjects. The threshold approach is used to classify EEG signals, with the feature employed being the amplitude of the EEG signal. The highest threshold value for the blinking signal was 0.6 mV with an accuracy of 97.9%, while the best threshold value for jaw contraction was 0.4 mV with an accuracy of 93.34 percent. The healthy, inexperienced participants took part in system testing. The total results of testing each robot movement yielded an overall success rate of 84.52 percent. Therefore, it was determined that the system could facilitate the operation of the length robot even if the user lacked prior experience with EEG-based systems.","PeriodicalId":148401,"journal":{"name":"2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114628215","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: 0

Conference Committees ACIRS 2023 会议委员会ACIRS 2023

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/acirs58671.2023.10239707

引用次数: 0

Enhancing Biomedical Education with Real-Time Object Identification through Augmented Reality 通过增强现实增强实时目标识别的生物医学教育

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/ACIRS58671.2023.10239781

Dinali Nelushi Jayawardana, Ruth Agada, Jie Yan

{"title":"Enhancing Biomedical Education with Real-Time Object Identification through Augmented Reality","authors":"Dinali Nelushi Jayawardana, Ruth Agada, Jie Yan","doi":"10.1109/ACIRS58671.2023.10239781","DOIUrl":"https://doi.org/10.1109/ACIRS58671.2023.10239781","url":null,"abstract":"This paper introduces a mobile augmented reality (AR) platform aimed at training first and second-year STEM majors in college, specifically focusing on the identification and usage of laboratory instruments. The platform addresses the challenges faced by students in introductory STEM courses and utilizes computer vision and AR technologies to create an engaging and learner-centric teaching environment. The platform incorporates features such as a knowledge test, guided navigation using Google Map API, and the ability to build a library of laboratory instruments through augmented reality. Developed using the Unity 3D Game engine and ARkit-XR plugin, the platform currently identifies six laboratory instruments in the biology department, with plans for expansion. The target audience comprises freshman biology majoring and minoring students at the university. The application will be integrated as a pre-lab activity during the semester, requiring the use of specialized equipment. The effectiveness of the platform will be evaluated through a user study conducted within introductory biology courses. This mobile AR platform caters to a specific market niche, addressing the existing resource gap at the university and aiming to enhance the learning experience for biomedical students. Future research will focus on expanding the platform to include chemistry and physics labs while incorporating additional functionalities to deepen students' understanding of laboratory instruments and improve the overall learning environment.","PeriodicalId":148401,"journal":{"name":"2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116685843","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: 0

Hydrodynamics Simulation of a Dual Fin Propelled Biomimetic Amphibious Robot 双鳍推进仿生两栖机器人的流体动力学仿真

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/ACIRS58671.2023.10240298

Minghai Xia, Qian Yin, Qunwei Zhu, Shanjun Chen, Jianzhong Shang, Zirong Luo

引用次数: 0

Copyright Page 版权页

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/acirs58671.2023.10240880

引用次数: 0

Automated Sorting System for Tahiti Lemons Using Raspberry PI 大溪地柠檬树莓派自动分拣系统

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/ACIRS58671.2023.10239685

Carlos Janampa-Paitan, Jose Elias Flores-Llallico, Brayan Freddy Orellana-Garcia, Herbert Antonio Vilchez-Baca

引用次数: 0

Research on Robot Accuracy Compensation Method Based on Modified Grey Wolf Algorithm 基于改进灰狼算法的机器人精度补偿方法研究

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/ACIRS58671.2023.10239812

Tianchen Peng, Tao Zhang, Zejun Sun

引用次数: 0

UUV Target Tracking Path Planning Algorithm Based on Deep Reinforcement Learning 基于深度强化学习的UUV目标跟踪路径规划算法

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/ACIRS58671.2023.10240259

You Yue, Wang Hao, Guanjie Hao, Yao Yao

引用次数: 0

The Application and Inspiration of Robots in the US Military 机器人在美军中的应用与启示

2023 8th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Pub Date : 2023-07-07 DOI: 10.1109/ACIRS58671.2023.10239710

Chenggong Zhai, Pinghua Zhang, Hongsi Xu, Xingguang Yuan, Liyong Zhou, Rangmin Wu

引用次数: 0