Science Robotics最新文献

{"title":"Advances, challenges, and opportunities for legged robots","authors":"Jonas Frey,&nbsp;Matías Mattamala,&nbsp;Hae-Won Park,&nbsp;Mayank Mittal,&nbsp;Georg Martius,&nbsp;Maike Osborne,&nbsp;Robert Sparrow,&nbsp;Marco Hutter","doi":"10.1126/scirobotics.aee0787","DOIUrl":"10.1126/scirobotics.aee0787","url":null,"abstract":"<div >Humanoid and quadrupedal robots have the potential to revolutionize the way we work, interact, and coexist with intelligent machines. To understand their effects on society and how they can enable scientific discovery, we assess the current capabilities of these systems along hardware, locomotion, autonomy, data, and applications. We identify recent advances and key open challenges that must be overcome to enable widespread adoption and new use cases for legged robots. Last, we provide an outlook on the future of legged robots, exploring their ethical considerations, economic potential, policy implications, and broader societal effects.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148596484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multilevel dynamics of the brain, hormones, mind, and behavior in social human-robot interaction","authors":"Yigit Topoglu,&nbsp;Frank Krueger,&nbsp;Shawn Joshi,&nbsp;Nina Rothstein,&nbsp;Adrian A. Franke,&nbsp;Xingnan Li,&nbsp;Jonathan Gratch,&nbsp;Ewart J. de Visser,&nbsp;Hasan Ayaz","doi":"10.1126/scirobotics.aec1762","DOIUrl":"10.1126/scirobotics.aec1762","url":null,"abstract":"<div >As robots enter homes, workplaces, and health care settings, sustaining trust during social interaction becomes a central challenge for human-robot interaction. However, relatively little is known about how humans integrate signals across the brain, hormones, mind, and behavior when robots violate expectations or display social expressiveness. Addressing this gap, we examined how robot performance (congruent versus erroneous) and expressiveness (animated versus stationary) shape multilevel human responses during face-to-face decision-making with an embodied humanoid robot. Participants engaged with the robot in person while neural activity was monitored using functional near-infrared spectroscopy, alongside salivary oxytocin assays, self-reported trust, and behavioral influence measures. Robot errors, implemented as cooperative norm violations, reliably reduced trust and influence, establishing performance reliability as the foundation of trust. Expressiveness amplified these effects: Animated robots elicited stronger prefrontal engagement and cross-level neural-hormonal coupling. Elevated oxytocin was most strongly linked to reduced trust during expressive robot errors, alongside diminished behavioral influence. This pattern is consistent with a context-sensitive vigilance response, indicating that oxytocin in human-robot interaction may heighten sensitivity to norm violations rather than reliably promote bonding. Validation analyses provided small, directionally consistent support for this pattern under counterbalanced order and improved temporal separation. Together, these findings establish a multilevel framework for studying trust in human-robot interaction and reveal a critical design trade-off: Expressive design enhances engagement but can make robot errors disproportionately damaging to trust. These insights identify a biologically grounded boundary condition for oxytocin’s role in social interaction and inform the design of socially effective and trustworthy robots.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.science.org/doi/reader/10.1126/scirobotics.aec1762","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148596498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward measurement of muscle forces during movement","authors":"Tian Tan,&nbsp;McKenzie S. White,&nbsp;Scott L. Delp","doi":"10.1126/scirobotics.aej8562","DOIUrl":"10.1126/scirobotics.aej8562","url":null,"abstract":"<div >Ultra-wideband radar identifies components of a muscle’s contractile state to estimate muscle force.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148617445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward measurement of muscle forces during movement","authors":"Tian Tan,&nbsp;McKenzie S. White,&nbsp;Scott L. Delp","doi":"10.1126/scirobotics.aej8562","DOIUrl":"10.1126/scirobotics.aej8562","url":null,"abstract":"<div >Ultra-wideband radar identifies components of a muscle’s contractile state to estimate muscle force.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148617446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is a robot a tool or an agent?","authors":"Robin R. Murphy","doi":"10.1126/scirobotics.aej9331","DOIUrl":"10.1126/scirobotics.aej9331","url":null,"abstract":"<div >The distinction is a matter of life and death to both a predator and a robot in the 2025 movie <i>Predator: Badlands</i>.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148596439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultra-wideband radar to measure in vivo muscle forces","authors":"Christopher S. Bird,&nbsp;Antonio P. L. Bo,&nbsp;Wei Lu,&nbsp;Taylor J. M. Dick","doi":"10.1126/scirobotics.aed5865","DOIUrl":"10.1126/scirobotics.aed5865","url":null,"abstract":"<div >Accurate measures of muscle forces are critical for engineers, clinicians, and biomechanists, yet direct measurement is highly invasive, and current estimation methods remain limited in accuracy. Here, we demonstrate the application of ultra-wideband radar sensors to noninvasively estimate muscle forces by measuring changes in the electromagnetic properties of contracting muscles, in muscles with different structural properties, during various static and dynamic conditions, and in the presence of fatigue. First, we show that ultra-wideband radar scans of muscle can reliably track isometric force in a unipennate knee extensor (vastus lateralis) and a bipennate ankle dorsiflexor (tibialis anterior). Next, we integrate radar signals in machine learning and linear models to estimate muscle forces during fatiguing isometric and dynamic knee extension contractions, with exceptional accuracy. Last, we identify radar frequency–dependent effects of the relationship between muscle forces and ultra-wideband radar signals, with these effects being independent of physiological and structural features known to influence muscle force. Together, these findings establish ultra-wideband radar as a noninvasive sensor capable of quantifying in vivo muscle forces, with the potential for wearable assistive technologies, biomechanics, and rehabilitation.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148596440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond imitation: Robots that learn to work in the real world","authors":"Johannes A. Stork","doi":"10.1126/scirobotics.aei2397","DOIUrl":"10.1126/scirobotics.aei2397","url":null,"abstract":"<div >Real-world learning can push robot manipulation beyond imitation alone.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148552647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinspired multimodal robotics","authors":"Ziyu Ren,&nbsp;Youning Duo,&nbsp;Haoyuan Xu,&nbsp;Yihui Zhang,&nbsp;Xingjian Liu,&nbsp;Jamie Paik,&nbsp;Auke Ijspeert,&nbsp;Li Wen","doi":"10.1126/scirobotics.aea7639","DOIUrl":"10.1126/scirobotics.aea7639","url":null,"abstract":"<div >To survive in dynamic and unstructured environments, animals have developed extraordinary multimodal locomotion capabilities. This biological insight drives the innovation of bioinspired multimodal robots, which are defined as robotic systems integrating and transitioning between two or more distinct modes of bioinspired locomotion. This Review explores the historical progression, key design considerations, and current challenges faced in the realm of multimodal robotics. We highlight recent advancements in robotic body design, including the integration of soft materials, innovative structure repurposing strategies, and the deployment of multirobot systems. These advancements facilitate seamless mode transitions through both active and passive structural reconfigurations. In the realm of path planning and motion control, the paradigm is progressively shifting from traditional graph-based approaches and discrete controllers to learning-based frameworks. To address the current void of standardized benchmarks in this field, we propose five performance metrics—number of modes, marginal cost of modality, component repurpose percentage, transition cost, and performance improvement—that provide a quantitative framework for evaluating multimodal robots in terms of design effectiveness and operational performance. Last, we delineate a strategic roadmap for the future that advocates for the integration of physical and computational intelligence in multimodal robotics, arguing that this convergence is crucial for enabling real-time behavioral adaptations to complex environmental stimuli and thereby enhancing the robustness and functionality of multimodal robotic systems.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148552646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performant robotic manipulation with real-world reinforcement learning","authors":"Kun Lei,&nbsp;Huanyu Li,&nbsp;Dongjie Yu,&nbsp;Zhenyu Wei,&nbsp;Lingxiao Guo,&nbsp;Zhennan Jiang,&nbsp;Ziyu Wang,&nbsp;Shiyu Liang,&nbsp;Huazhe Xu","doi":"10.1126/scirobotics.aed6267","DOIUrl":"10.1126/scirobotics.aed6267","url":null,"abstract":"<div >Real-world robotic manipulation in homes and factories demands reliability, efficiency, and robustness that approach or surpass skilled human operators. We present a real-world reinforcement learning (RL) framework, RL-100, for achieving complete task success under a predefined evaluation protocol built on diffusion visuomotor policies. RL-100 unifies imitation and RL under a single clipped proximal policy optimization surrogate objective applied in the denoising process, yielding conservative, stable improvements across offline and online stages. To meet deployment latency, a lightweight consistency distillation compresses multistep diffusion into a one-step controller for high-frequency control. The framework is task, embodiment, and representation agnostic and supports both single-action and action-chunking control. We evaluated RL-100 on eight diverse real-robot tasks, from pushing and bowling to pouring, cloth folding, unscrewing, multistage juicing, and long-horizon box folding. Under our predefined protocol, RL-100 achieved 100% success in the evaluated trials (1000 of 1000 episodes), including up to 250 of 250 consecutive trials on one task. It matched or surpassed expert teleoperators in time to completion. Without retraining, a single policy attained ∼90% zero-shot success under environmental and dynamics shifts, adapted in a few-shot regime to substantial task variations (86.7%), and remained robust to human perturbations (about 96%). Our juicing robot served customers continuously for about 7 hours without failure when deployed zero-shot in a shopping mall. These results suggest a potential path to deployable robot learning by starting from human priors, aligning training objectives with human-grounded metrics, and reliably extending performance beyond human demonstrations.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.science.org/doi/reader/10.1126/scirobotics.aed6267","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148552767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Allocentric teleoperation for variable perspective multirobot coordination","authors":"Constantin Uhde,&nbsp;Nicolas Berberich,&nbsp;Simon Armleder,&nbsp;Florian Bergner,&nbsp;Gordon Cheng","doi":"10.1126/scirobotics.adz7130","DOIUrl":"10.1126/scirobotics.adz7130","url":null,"abstract":"<div >The human brain can process spatial action through either egocentric (self-centered) or allocentric (environment-centered) perspectives. Despite this cognitive ability, teleoperation of robotic systems has been predominantly egocentric, wherein operators control a single robot from an inside-out perspective with limited situational overview. This paper proposes a scalable paradigm for simultaneously teleoperating multiple robotic systems from an allocentric perspective that enables a single operator to solve complex collaborative tasks. The perceptual information of all robots is fused into a joint virtual environment, which the operator can view from a top-down perspective to control the robots similar to puppets. We investigated differences between egocentric and allocentric multirobot teleoperation using both simulated and real robots. In the simulation study, study participants (<i>n</i> = 15) reported a higher sense of embodiment over robot bodies when using egocentric control, enabling them to perform more precise manipulation after initial training. Using allocentric control, participants achieved speed increases of 84% in a parallelizable locomotion task and 50% in a situational overview task compared with egocentric control. Participants reported improved system usability and overview with allocentric control, and no significant differences in sense of agency were measured. These results were validated in a real-world study with two physical robots (<i>n</i> = 6) and underscore the effectiveness of our allocentric teleoperation framework as a complementary approach to egocentric robotic teleoperation. Interfaces that support smooth switching between allocentric and egocentric control therefore enable operators to leverage the advantages of both paradigms depending on their specific task.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 116","pages":""},"PeriodicalIF":25.5,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148441408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}