International Journal of Humanoid Robotics最新文献

{"title":"Hybrid_ASL: Cross-Domain Transfer Learning for High-Accuracy American Sign Language Recognition","authors":"Haoming Yi","doi":"10.1142/s0219843625400195","DOIUrl":"https://doi.org/10.1142/s0219843625400195","url":null,"abstract":"Communication is one of the issues that people with hearing impairments constantly have to struggle with; this is partly because advanced assistive devices are not widely available and used. These obstacles often hinder access to essential services and the ability to engage in meaningful communication. To address this gap, the current paper presents Hybrid_ASL, a novel architecture based on deep learning specifically designed to enhance the recognition of American Sign Language (ASL) hand gestures. Hybrid_ASL utilizes the concept of cross-domain transfer learning, enabling the model to transfer visual knowledge gained from large-scale datasets to the problem-specific task of ASL classification. The model structure combines convolutional and transformer-based modules, thereby capturing both local spatial patterns and long-range contextual relationships. The training pipeline involves pre-training the model using a large number of images of ASL ([Formula: see text] 87,000), which are annotated with labels. The model is then trained through a fine-tuning process, allowing for optimization of classification accuracy while preserving computational efficiency. The presented dual-phase training method can be applied to models, yielding a significant improvement in model operation, albeit with prohibitively large computational requirements. The results of the empirical analysis demonstrate that Hybrid_ASL achieves excellent performance, with an accuracy of 99.98% and comparable levels of precision, recall, and F1-scores. Not only do these results outperform those of standard convolutional neural networks (e.g., ResNet, EfficientNet), but they also show that the integration of transfer learning with adaptive model refinement is effective. Ultimately, this study demonstrates the potential adaptability of Hybrid_ASL in the development of intelligent and scalable assistive technology. The model will enhance the accessibility of communication and the overall quality of life for the deaf and hard-of-hearing community, as it provides nearly flawless ASL recognition capabilities.","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147892385","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}

{"title":"Task-Oriented Self-Imitation Learning for Robotic Autonomous Skill Acquisition","authors":"Chenyang Ran, Jianbo Su","doi":"10.1142/s0219843624500014","DOIUrl":"https://doi.org/10.1142/s0219843624500014","url":null,"abstract":"<p>The inferior sample efficiency of reinforcement learning (RL) and the requirement for high-quality demonstrations in imitation learning (IL) will hinder their application in real-world robots. To address this challenge, a novel self-evolution framework, named task-oriented self-imitation learning (TOSIL), is proposed. To circumvent external demonstrations, the top-K self-generated trajectories are chosen as expert data from both per-episode exploration and long-term return perspectives. Each transition is assigned a guide reward, which is formulated by these trajectories. The guide rewards update as the agent evolves, encouraging good exploration behaviors. This methodology guarantees that the agent explores in the direction relevant to the task, improving sample efficiency and asymptotic performance. The experimental results on locomotion and manipulation tasks indicate that the proposed framework outperforms other state-of-the-art RL methods. Furthermore, the integration of suboptimal trajectories has the potential to improve the sample efficiency while maintaining performance. This is a significant advancement in autonomous skill acquisition for robots.</p>","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140153545","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}

{"title":"Celebrating 20th Anniversary of IJHR","authors":"Ming Xie, John Weng, Giulio Sandini","doi":"10.1142/s021984362402002x","DOIUrl":"https://doi.org/10.1142/s021984362402002x","url":null,"abstract":"<p>In this editorial dedicated to the special issue which celebrates the 20th anniversary of the International Journal of Humanoid Robotics (IJHR), we outline the history of IJHR.</p>","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":"15 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140197941","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}

{"title":"Anthology: Cognitive Developmental Humanoids Robotics","authors":"Minoru Asada","doi":"10.1142/s0219843624500026","DOIUrl":"https://doi.org/10.1142/s0219843624500026","url":null,"abstract":"<p>This paper explores the confluence of physical embodiment and social interaction in the context of Cognitive Developmental Humanoid Robotics (CDHR). By classifying varied interactions through developmental stages of the “self” and their interaction spheres, the discussion unearths profound insights into the composite nature of developmental processes. It presents a multi-dimensional exploration through different interaction scenarios, ranging from fetus-mother interactions to advanced large language models like ChatGPT, revealing the intrinsic connection between the physical and social realms of existence. In conclusion, this paper broadens the horizon of our understanding of the intricate interplays between physical embodiment and social interaction, setting the stage for more nuanced, ethically sound approaches and explorations in the realm of humanoid robotics and artificial intelligence.</p>","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":"9 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140197936","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}

{"title":"Learning an Image-Based Visual Servoing Controller for Object Grasping","authors":"Shuaijun Wang, Lining Sun, Mantian Li, Pengfei Wang, Fusheng Zha, Wei Guo, Qiang Li","doi":"10.1142/s0219843623500330","DOIUrl":"https://doi.org/10.1142/s0219843623500330","url":null,"abstract":"<p>Adaptive and cooperative control of arms and fingers for natural object reaching and grasping, without explicit 3D geometric pose information, is observed in humans. In this study, an image-based visual servoing controller, inspired by human grasping behavior, is proposed for an arm-gripper system. A large-scale dataset is constructed using Pybullet simulation, comprising paired images and arm-gripper control signals mimicking expert grasping behavior. Leveraging this dataset, a network is directly trained to derive a control policy that maps images to cooperative grasp control. Subsequently, the learned synergy grasping policy from the network is directly applied to a real robot with the same configuration. Experimental results demonstrate the effectiveness of the algorithm. Videos can be found at https://www.bilibili.com/video/BV1tg4y1b7Qe/.</p>","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":"51 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140153453","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}

{"title":"Conscious Learning without Post-Selection Misconduct","authors":"Juyang Weng","doi":"10.1142/s0219843623500317","DOIUrl":"https://doi.org/10.1142/s0219843623500317","url":null,"abstract":"","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":"31 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138995972","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}

{"title":"C-SQG: Cosine-Law-Based Spatially Quantized Gait Generation for Knee-Stretched Biped Walking","authors":"Chaobin Zou, Rui Huang, Guangkui Song, Kecheng Shi, Zhinan Peng, Hong Cheng","doi":"10.1142/s0219843623500329","DOIUrl":"https://doi.org/10.1142/s0219843623500329","url":null,"abstract":"","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":"85 3","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138998220","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}

{"title":"ZMP - where are we after fifty-five years?","authors":"B. Borovac, M. Nikolic, M. Raković, S. Savic","doi":"10.1142/s0219843623500305","DOIUrl":"https://doi.org/10.1142/s0219843623500305","url":null,"abstract":"","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":"173 ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139010688","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}

{"title":"From embodiment to super-embodiment: an approach to open-ended and human aligned intelligence/mind","authors":"Yasuo Kuniyoshi","doi":"10.1142/s0219843623500299","DOIUrl":"https://doi.org/10.1142/s0219843623500299","url":null,"abstract":"","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":" 34","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138616351","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}

{"title":"Avatar","authors":"Hiroshi Ishiguro","doi":"10.1142/s0219843623500287","DOIUrl":"https://doi.org/10.1142/s0219843623500287","url":null,"abstract":"","PeriodicalId":50319,"journal":{"name":"International Journal of Humanoid Robotics","volume":"109 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139245675","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}