Science Robotics最新文献

Extending robot minds through collective learning 通过集体学习扩展机器人的思维

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-24 DOI: 10.1126/scirobotics.adv4049

Amanda Prorok

引用次数: 0

Accelerating discovery in natural science laboratories with AI and robotics: Perspectives and challenges 利用人工智能和机器人技术加速自然科学实验室的发现：观点和挑战

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-24 DOI: 10.1126/scirobotics.adv7932

Andrew I. Cooper, Patrick Courtney, Kourosh Darvish, Moritz Eckhoff, Hatem Fakhruldeen, Andrea Gabrielli, Animesh Garg, Sami Haddadin, Kanako Harada, Jason Hein, Maria Hübner, Dennis Knobbe, Gabriella Pizzuto, Florian Shkurti, Ruja Shrestha, Kerstin Thurow, Rafael Vescovi, Birgit Vogel-Heuser, Ádám Wolf, Naruki Yoshikawa, Yan Zeng, Zhengxue Zhou, Henning Zwirnmann

引用次数: 0

Lowly fly or impressive miniature robot? 卑微的苍蝇还是令人印象深刻的微型机器人？

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-24 DOI: 10.1126/scirobotics.aeb6685

Robin R. Murphy

引用次数: 0

Miniature magneto-ultrasonic machines for wireless robotic sensing and manipulation 用于无线机器人传感和操作的微型磁超声机

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-17 DOI: 10.1126/scirobotics.adu4851

Xurui Liu, Hanchuan Tang, Na Li, Linjie He, Ye Tian, Bo Hao, Junnan Xue, Chaoyu Yang, Joseph Jao Yiu Sung, Li Zhang, Jianfeng Zang

{"title":"Miniature magneto-ultrasonic machines for wireless robotic sensing and manipulation","authors":"Xurui Liu, Hanchuan Tang, Na Li, Linjie He, Ye Tian, Bo Hao, Junnan Xue, Chaoyu Yang, Joseph Jao Yiu Sung, Li Zhang, Jianfeng Zang","doi":"10.1126/scirobotics.adu4851","DOIUrl":"10.1126/scirobotics.adu4851","url":null,"abstract":"<div >Intelligent miniature systems capable of wireless sensing and manipulation hold considerable promise for advancing biomedical applications. However, the development of these systems has been substantially hindered by sensing-actuation incompatibility at small scales. To overcome this challenge, we propose a robotic sensing approach that integrates embedded ultrasonic soft sensors (EUSSs) with magnetic actuators, resulting in a wireless sensor-integrated miniature machine with seamless integration and minimal interference between fields. The EUSS, with its compact dimensions (1.3 millimeters by 1.3 millimeters by 1.6 millimeters), softness (98 kilopascals), and lightweight design (4.6 milligrams), is compatible with both soft and rigid components in terms of deformability and size. By engineering onboard transducers and using passive ultrasound communication along with external magnetic fields, we could wirelessly detect and regulate environmental parameters such as force, vibration, viscosity, and temperature. Demonstrations in rabbit and porcine models show the potential for robotic feedback control, accurate drug dosing, and in situ physiological monitoring, paving the way for real-world applications of intelligent miniature machines.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"10 106","pages":""},"PeriodicalIF":27.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145077510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Arm prosthesis with dexterous control and sensory feedback delivers winning performance at Cybathlon 手臂假体与灵巧的控制和感官反馈提供胜利的表现在Cybathlon。

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-17 DOI: 10.1126/scirobotics.aea9377

Xuhui Hu, Aiguo Song, Min Xu

引用次数: 0

BCIT’s BEAST wheelchair takes on Cybathlon with power, precision, and pilot-led design BCIT的野兽轮椅以动力，精度和飞行员主导的设计承担Cybathlon。

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-17 DOI: 10.1126/scirobotics.aeb1340

Garrett Kryt, Rory Dougall, Jaimie Borisoff

引用次数: 0

A review of learning-based dynamics models for robotic manipulation 基于学习的机器人操作动力学模型综述

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-17 DOI: 10.1126/scirobotics.adt1497

Bo Ai, Stephen Tian, Haochen Shi, Yixuan Wang, Tobias Pfaff, Cheston Tan, Henrik I. Christensen, Hao Su, Jiajun Wu, Yunzhu Li

{"title":"A review of learning-based dynamics models for robotic manipulation","authors":"Bo Ai, Stephen Tian, Haochen Shi, Yixuan Wang, Tobias Pfaff, Cheston Tan, Henrik I. Christensen, Hao Su, Jiajun Wu, Yunzhu Li","doi":"10.1126/scirobotics.adt1497","DOIUrl":"10.1126/scirobotics.adt1497","url":null,"abstract":"<div >Dynamics models that predict the effects of physical interactions are essential for planning and control in robotic manipulation. Although models based on physical principles often generalize well, they typically require full-state information, which can be difficult or impossible to extract from perception data in complex, real-world scenarios. Learning-based dynamics models provide an alternative by deriving state transition functions purely from perceived interaction data, enabling the capture of complex, hard-to-model factors and predictive uncertainty and accelerating simulations that are often too slow for real-time control. Recent successes in this field have demonstrated notable advancements in robot capabilities, including long-horizon manipulation of deformable objects, granular materials, and complex multiobject interactions such as stowing and packing. A crucial aspect of these investigations is the choice of state representation, which determines the inductive biases in the learning system for reduced-order modeling of scene dynamics. This article provides a timely and comprehensive review of current techniques and trade-offs in designing learned dynamics models, highlighting their role in advancing robot capabilities through integration with state estimation and control and identifying critical research gaps for future exploration.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"10 106","pages":""},"PeriodicalIF":27.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145077693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Robotic reading companions can mitigate oral reading anxiety in children 机器人阅读同伴可以减轻儿童的口语阅读焦虑

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-10 DOI: 10.1126/scirobotics.adu5771

Lauren L. Wright, Pooja Vegesna, Joseph E. Michaelis, Bilge Mutlu, Sarah Sebo

{"title":"Robotic reading companions can mitigate oral reading anxiety in children","authors":"Lauren L. Wright, Pooja Vegesna, Joseph E. Michaelis, Bilge Mutlu, Sarah Sebo","doi":"10.1126/scirobotics.adu5771","DOIUrl":"10.1126/scirobotics.adu5771","url":null,"abstract":"<div >Reading fluency is a vital building block for developing literacy, yet the best way to practice fluency—reading aloud—can cause anxiety severe enough to inhibit literacy development in ways that can have an adverse effect on students through adulthood. One promising intervention to mitigate oral reading anxiety is to have children read aloud to a robot. Although observations in prior work have suggested that people likely feel more comfortable in the presence of a robot instead of a human, few studies have empirically demonstrated that people feel less anxious performing in front of a robot compared with a human or used objective physiological indicators to identify decreased anxiety. To investigate whether a robotic reading companion could reduce reading anxiety felt by children, we conducted a within-subjects study where children aged 8 to 11 years (<i>n</i> = 52) read aloud to a human and a robot individually while being monitored for physiological responses associated with anxiety. We found that children exhibited fewer physiological indicators of anxiety, specifically vocal jitter and heart rate variability, when reading to the robot compared with reading to a person. This paper provides strong evidence that a robot’s presence has an effect on the anxiety a person experiences while doing a task, offering justification for the use of robots in a wide-reaching array of social interactions that may be anxiety inducing.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"10 106","pages":""},"PeriodicalIF":27.5,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145028467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Observing a robot peer’s failures facilitates students’ classroom learning 观察机器人同伴的失败有助于学生的课堂学习

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-10 DOI: 10.1126/scirobotics.adu5257

Liuqing Chen, Yu Cai, Yuyang Fang, Ziqi Yang, Duowei Xia, Jiaxiang You, Shuhong Xiao, Yaxuan Song, Lingwei Zhan, Juanjuan Chen, Lingyun Sun

{"title":"Observing a robot peer’s failures facilitates students’ classroom learning","authors":"Liuqing Chen, Yu Cai, Yuyang Fang, Ziqi Yang, Duowei Xia, Jiaxiang You, Shuhong Xiao, Yaxuan Song, Lingwei Zhan, Juanjuan Chen, Lingyun Sun","doi":"10.1126/scirobotics.adu5257","DOIUrl":"10.1126/scirobotics.adu5257","url":null,"abstract":"<div >According to productive failure (PF) theory, experiencing failure during problem-solving can enhance students’ knowledge acquisition in subsequent instruction. However, challenging students with problems beyond their current capabilities may strain their skills, prior knowledge, and emotional well-being. To address this, we designed a social robot–assisted teaching activity in which students observed a robot’s unsuccessful problem-solving attempts, offering a PF-like preparatory effect without requiring direct failure. We conducted two classroom-based studies in a middle school setting to evaluate the method’s effectiveness. In study 1 (<i>N</i> = 135), we compared three instructional methods—observing robot failure (RF), individual problem-solving failure, and direct instruction—in an eighth-grade mathematics lesson. Students in the RF condition showed the greatest gains in conceptual understanding and reported lower social pressure, although no significant differences were found in procedural knowledge or knowledge transfer. Follow-up study 2 (<i>N</i> = 110) further validated the method’s effectiveness in supporting knowledge acquisition after a 2-week robot-involved adaptation phase, when the novelty effect had largely subsided. Students confirmed their perception of the robot as a peer, and they offered positive evaluations of its intelligence and neutral views of its anthropomorphism. Our findings suggest that observing the robot’s failure has a comparable, or even greater, effect on knowledge acquisition than experiencing failure firsthand. These results underscore the value of social robots as peers in science, technology, engineering, and mathematics education and highlight the potential of integrating robotics with evidence-based teaching strategies to enhance learning outcomes.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"10 106","pages":""},"PeriodicalIF":27.5,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145028483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

How can educational robots enhance family life? Through careful integration 教育机器人如何改善家庭生活？通过精心整合

IF 27.5 1区计算机科学

Science Robotics Pub Date : 2025-09-10 DOI: 10.1126/scirobotics.adu6123

Joseph E. Michaelis, Bilge Mutlu

引用次数: 0