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International Journal of Humanoid Robotics最新文献

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Impact of Showing Robot Demonstration on Introducing Social Robotics Field to University Students 机器人演示对大学生介绍社会机器人领域的影响
4区 计算机科学 Q4 ROBOTICS Pub Date : 2023-09-29 DOI: 10.1142/s0219843623500184
Muhammad Yeza Baihaqi, Sendren Sheng-Dong Xu
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引用次数: 0
Design and control of a novel hydraulic driven humanoid hand 新型液压驱动仿人机械手的设计与控制
IF 1.5 4区 计算机科学 Q4 ROBOTICS Pub Date : 2023-08-17 DOI: 10.1142/s0219843623500159
Zhe Tao, Xu Li, Haibo Feng, Yili Fu
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引用次数: 0
Robust Walking and Running Gaits for Biped Robots with a QP-based Whole-Body Controller 基于QP的全身控制器实现两足机器人的稳健步行和跑步步态
IF 1.5 4区 计算机科学 Q4 ROBOTICS Pub Date : 2023-08-17 DOI: 10.1142/s0219843623500160
Qiuyue Luo, Y. Ou, Jianxin Pang, Ligang Ge, C. Fu
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引用次数: 0
A Heuristics-Based Reinforcement Learning Method to Control Bipedal Robots 基于启发式强化学习的双足机器人控制方法
IF 1.5 4区 计算机科学 Q4 ROBOTICS Pub Date : 2023-08-11 DOI: 10.1142/s0219843623500135
Daoling Qin, Guoteng Zhang, Zhengguo Zhu, T. Chen, Weiliang Zhu, Xuewen Rong, Anhuan Xie, Yibin Li
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引用次数: 0
Reinforcement Learning-Based Approach to Robot Path Tracking in Nonlinear Dynamic Environments 基于强化学习的非线性动态环境下机器人路径跟踪方法
IF 1.5 4区 计算机科学 Q4 ROBOTICS Pub Date : 2023-08-11 DOI: 10.1142/s0219843623500147
Wei Chen, Zebin Zhou
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引用次数: 0
Advancements in Agricultural Automation: A Comprehensive Review of Artificial Intelligence and Humanoid Robotics in Farming 农业自动化的进展:人工智能和类人机器人在农业中的综合综述
IF 1.5 4区 计算机科学 Q4 ROBOTICS Pub Date : 2023-08-10 DOI: 10.1142/s0219843623500123
Arockia Selvakumar Arockia Doss, Abarna Jeyabalan, Priti Rekha Borah, Pavan Kalyan Lingampally, Ing. Daniel Schilberg
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引用次数: 0
Analysis and Optimization of Gait Cycle of 25-dof NAO Robot using Particle Swarm Optimization and Genetic Algorithms 基于粒子群优化和遗传算法的25自由度NAO机器人步态周期分析与优化
IF 1.5 4区 计算机科学 Q4 ROBOTICS Pub Date : 2023-06-30 DOI: 10.1142/s0219843623500111
Pushpendra Gupta, D. K. Pratihar, K. Deb
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引用次数: 0
Stable Walking Feedback Control for a Self-Balance Lower Body Exoskeleton for Paraplegics 截瘫患者下半身外骨骼自平衡的稳定行走反馈控制
IF 1.5 4区 计算机科学 Q4 ROBOTICS Pub Date : 2023-05-18 DOI: 10.1142/s0219843623500068
Jinke Li, Dingkui Tian, Jianquan Sun, Meng Yin, Zhuo Wang, Xin Wu
{"title":"Stable Walking Feedback Control for a Self-Balance Lower Body Exoskeleton for Paraplegics","authors":"Jinke Li, Dingkui Tian, Jianquan Sun, Meng Yin, Zhuo Wang, Xin Wu","doi":"10.1142/s0219843623500068","DOIUrl":"https://doi.org/10.1142/s0219843623500068","url":null,"abstract":"","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44850457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Person Re-Identification Based on Feature Fusion in Ai System 基于特征融合的人工智能系统人物再识别
IF 1.5 4区 计算机科学 Q4 ROBOTICS Pub Date : 2023-03-24 DOI: 10.1142/s0219843623500044
Sixian Chan, Yating Liu, Xiaotian Pan, Yanjing Lei
{"title":"Person Re-Identification Based on Feature Fusion in Ai System","authors":"Sixian Chan, Yating Liu, Xiaotian Pan, Yanjing Lei","doi":"10.1142/s0219843623500044","DOIUrl":"https://doi.org/10.1142/s0219843623500044","url":null,"abstract":"","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42631463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial Intelligence Combined with Deep Learning in Film and Television Quality Education for the Youth 人工智能与深度学习相结合的青少年影视素质教育
IF 1.5 4区 计算机科学 Q4 ROBOTICS Pub Date : 2022-11-26 DOI: 10.1142/s0219843622500190
Dong Huang, Jong Hoon-Yang
Today, with the rapid development of science and technology, the value of education is more and more valued by people, but the research and development of quality education in film and television are still relatively traditional. The objective is to explore the application and effect of the combination of artificial intelligence and deep learning algorithm in the quality education of youth film and television. In view of the current problems in the quality education of film and television, this work innovatively introduces the augmented reality (AR) technology, and applies artificial intelligence and AR technology to the quality education of film and television for young people. At the same time, a deep learning algorithm is introduced to build a youth film and television quality education system based on artificial intelligence combined with deep learning, and further empirical analysis of the system is carried out in the form of a questionnaire survey. The questionnaire survey shows that, from the perspective of various dimensions of learning attitude, the two groups of learners had significant differences in emotional experience and self-cognition ([Formula: see text]), and more than 90% of the teenagers thought the system resource interface was beautiful; from the perspective of the perceived usefulness of the system, 68.24% of the teenagers believe that the system is easy to operate and useful, and as many as 82.82% of the teenagers believe that the system improves their interest in learning about quality education courses in film and television. Therefore, it is found that the constructed system can improve the learning interest of young people in the quality education course of film and television and make their learning attitude more positive, providing experimental reference for the latter research in the field of youth education.
在科技飞速发展的今天,教育的价值越来越被人们所重视,但是影视素质教育的研发还是比较传统的。目的是探索人工智能与深度学习算法相结合在青少年影视素质教育中的应用与效果。针对当前影视素质教育中存在的问题,本工作创新性地引入增强现实(AR)技术,将人工智能和AR技术应用于青少年影视素质教育中。同时,引入深度学习算法,构建基于人工智能与深度学习相结合的青少年影视素质教育体系,并以问卷调查的形式对该系统进行进一步的实证分析。问卷调查显示,从学习态度的各个维度来看,两组学习者在情感体验和自我认知方面存在显著差异([公式:见文]),90%以上的青少年认为系统资源界面美观;从系统的感知有用性来看,68.24%的青少年认为系统易于操作和有用,高达82.82%的青少年认为系统提高了他们学习影视素质教育课程的兴趣。因此,我们发现所构建的系统能够提高青少年在影视素质教育课程中的学习兴趣,使其学习态度更加积极,为后期在青少年教育领域的研究提供实验参考。
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引用次数: 0
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International Journal of Humanoid Robotics
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