Science Robotics最新文献

{"title":"Beyond alignment: Why robotic foundation models need context-aware safety.","authors":"Alexander Robey, Zachary Ravichandran, Eliot Krzysztof Jones, Jared Perlo, Fazl Barez, Vijay Kumar, J Zico Kolter, Hamed Hassani, George J Pappas","doi":"10.1126/scirobotics.aef2191","DOIUrl":"https://doi.org/10.1126/scirobotics.aef2191","url":null,"abstract":"<p><p>Because AI-enabled robots can be tricked into taking unsafe actions, they require layered, context-aware safety guardrails.</p>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 113","pages":"eaef2191"},"PeriodicalIF":27.5,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147790095","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}

{"title":"Transfer learning in robotics: From promises to practice through the emerging role of foundation models.","authors":"Michael C Welle, Noémie Jaquier, Andrej Gams, Jens Lundell, Danica Kragic","doi":"10.1126/scirobotics.aeh4374","DOIUrl":"https://doi.org/10.1126/scirobotics.aeh4374","url":null,"abstract":"<p><p>Foundation models offer a promising avenue to achieve transfer across robots, tasks, and environments.</p>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 113","pages":"eaeh4374"},"PeriodicalIF":27.5,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147790104","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}

{"title":"Dexterous grasping with an active palm","authors":"Amos Matsiko","doi":"10.1126/scirobotics.aei2046","DOIUrl":"10.1126/scirobotics.aei2046","url":null,"abstract":"<div >A tactile-responsive gripper with an active palm enables adaptive grasping and dexterous manipulation of objects.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 113","pages":""},"PeriodicalIF":27.5,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147790058","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}

{"title":"A retrieval-augmented framework enabling VLM spatial awareness for object-centric robot manipulation.","authors":"Kai Chen, Chengkun Li, Chang Tu, Jiahui Pan, Yiyao Ma, Wei Chen, Zhongxiang Zhou, Xuecheng Xu, Stephen James, Chi-Wing Fu, Rong Xiong, Pieter Abbeel, Yun-Hui Liu, Qi Dou","doi":"10.1126/scirobotics.aea2092","DOIUrl":"https://doi.org/10.1126/scirobotics.aea2092","url":null,"abstract":"<p><p>Connecting the semantic reasoning of vision-language models (VLMs) to the precise geometric demands of robotic manipulation remains a fundamental challenge. Although VLMs can interpret high-level commands, they lack the intrinsic spatial intelligence required for tasks demanding precise object placement, orientation, and physical reasoning. Here, we introduce Retrieval-Augmented Manipulation (RAM), an object-centric framework that endows general-purpose vision foundation models with the spatial reasoning necessary for robust manipulation. RAM bridges the semantic-to-geometric gap by grounding abstract concepts into an explicit, object-centric three-dimensional (3D) representation. This grounded information is then provided as augmented context to the VLM, empowering it to decompose complex instructions into a sequence of spatially precise and physically plausible subgoals. We demonstrate that RAM, in a zero-shot setting on a real-world robot, can execute these subgoals to fulfill complex spatial language instructions, complete spatially aware manipulation under the guidance of a single 2D image, and adaptively replan tasks by reasoning about physical constraints like object size and collisions. Quantitative evaluations on the Common Object in 3D (CO3D) dataset also validated that RAM's core vision module generalizes to previously unseen object categories and is robust to variations in shape and occlusions. By providing a structured bridge between semantic intent and geometric execution, RAM represents a critical step toward developing more physically intelligent and general-purpose robotic systems.</p>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 113","pages":"eaea2092"},"PeriodicalIF":27.5,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147790061","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}

{"title":"How foundation models will revolutionize robot swarms.","authors":"Volker Strobel, Marco Dorigo, Mario Fritz","doi":"10.1126/scirobotics.adz1543","DOIUrl":"https://doi.org/10.1126/scirobotics.adz1543","url":null,"abstract":"<p><p>Robot swarms are composed of many, typically simple, robots that accomplish complex tasks through local communication and decentralized coordination. Traditionally, robot controllers are designed before a mission using programming code. This process requires substantial development effort and limits the flexibility of the swarm. We discuss how onboard foundation models (FMs) could revolutionize this process through two complementary approaches. The first approach uses FMs as swarm designers to synthesize robot controllers and perform high-level planning. The second approach uses FMs as swarm operators to facilitate robot-robot collaboration and human-swarm interaction.</p>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 113","pages":"eadz1543"},"PeriodicalIF":27.5,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147790152","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}

{"title":"Robot farm elegy","authors":"Robin R. Murphy","doi":"10.1126/scirobotics.aeh3279","DOIUrl":"10.1126/scirobotics.aeh3279","url":null,"abstract":"<div >The 2025 novel <i>Mechanize My Hands for War</i> features humanoid robots for agriculture.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 113","pages":""},"PeriodicalIF":27.5,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147790107","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}

{"title":"From autonomy to alliance: Robotic foundation models must learn with us, not just for us","authors":"Sharmita Dey, Robert Riener, Strahinja Dosen, Stefano V. Albrecht","doi":"10.1126/scirobotics.aea1822","DOIUrl":"https://doi.org/10.1126/scirobotics.aea1822","url":null,"abstract":"This Viewpoint urges reimagining of robotic foundation models, from treating the robot as a solitary, omnipotent agent to embracing a multiagent, alliance-aware paradigm. Alliance-aware models learn with humans and other robots, not merely for them, by embedding mechanisms that foster social interaction and generalization across heterogeneous partners. We outline six design pillars that cultivate such collaborative intelligence: interaction priors, partner modeling (machine theory of mind), modular and composable policies, norm adaptation, trust-aware memory, and communication. Together, these pillars empower robots to fluidly switch social roles, adapt to unfamiliar collaborators, and coordinate robustly within dynamic multiagent ecologies spanning homes, factories, clinics, and field operations.","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"24 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147732336","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}

{"title":"Designing microrobots with embodied physical intelligence","authors":"Melisa Yashinski","doi":"10.1126/scirobotics.aei0811","DOIUrl":"10.1126/scirobotics.aei0811","url":null,"abstract":"<div >A flexible chain of 3D microprinted units exhibits emergent dynamics in response to environmental interactions.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"11 113","pages":""},"PeriodicalIF":27.5,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147733962","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}

{"title":"Object-centric task representation and transfer using diffused orientation fields","authors":"Cem Bilaloglu, Tobias Löw, Sylvain Calinon","doi":"10.1126/scirobotics.aea1762","DOIUrl":"https://doi.org/10.1126/scirobotics.aea1762","url":null,"abstract":"Curved objects pose a fundamental challenge for task transfer in robotics: Unlike planar surfaces, curved surfaces do not admit a global reference frame. As a result, task-relevant directions such as “toward” or “along” the surface vary with position and geometry, making object-centric tasks difficult to transfer across shapes. To address this, we introduce an approach using diffused orientation fields, a smooth representation of local reference frames, for expressing and transferring tasks across curved objects. By expressing manipulation tasks in these smoothly varying local frames, we reduce the problem of transferring tasks across curved objects to establishing sparse keypoint correspondences. Our representation is computed online from raw point cloud data using diffusion processes governed by partial differential equations, conditioned on keypoints. We evaluate our method under geometric, topological, and keypoint perturbations and demonstrate successful transfer of tasks requiring continuous physical interaction such as coverage, slicing, and peeling across varied objects.","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"68 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147732338","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}

{"title":"A careful examination of large behavior models for multitask dexterous manipulation","authors":"Jose Barreiros, Andrew Beaulieu, Aditya Bhat, Rick Cory, Eric Cousineau, Hongkai Dai, Ching-Hsin Fang, Kunimatsu Hashimoto, Muhammad Zubair Irshad, Masha Itkina, Naveen Kuppuswamy, Kuan-Hui Lee, Katherine Liu, Dale McConachie, Ian McMahon, Haruki Nishimura, Calder Phillips-Grafflin, Charles Richter, Paarth Shah, Krishnan Srinivasan, Blake Wulfe, Chen Xu, Mengchao Zhang, Alex Alspach, Maya Angeles, Kushal Arora, Vitor Campagnolo Guizilini, Alejandro Castro, Dian Chen, Ting-Sheng Chu, Sam Creasey, Sean Curtis, Richard Denitto, Emma Dixon, Eric Dusel, Matthew Ferreira, Aimee Goncalves, Grant Gould, Damrong Guoy, Swati Gupta, Xuchen Han, Kyle Hatch, Brendan Hathaway, Allison Henry, Hillel Hochsztein, Phoebe Horgan, Shun Iwase, Donovon Jackson, Siddharth Karamcheti, Sedrick Keh, Joseph Masterjohn, Masayuki Masuda, Jean Mercat, Patrick Miller, Paul Mitiguy, Tony Nguyen, Jeremy Nimmer, Yuki Noguchi, Reko Ong, Aykut Onol, Owen Pfannenstiehl, Richard Poyner, Leticia Priebe Mendes Rocha, Gordon Richardson, Christopher Rodriguez, Derick Seale, Michael Sherman, Mariah Smith-Jones, David Tago, Pavel Tokmakov, Matthew Tran, Basile Van Hoorick, Igor Vasiljevic, Sergey Zakharov, Mark Zolotas, Rareș Ambruș, Kerri Fetzer-Borelli, Benjamin Burchfiel, Hadas Kress-Gazit, Siyuan Feng, Stacie Ford, Russ Tedrake","doi":"10.1126/scirobotics.aea6201","DOIUrl":"https://doi.org/10.1126/scirobotics.aea6201","url":null,"abstract":"Robot manipulation has seen tremendous progress in recent years, with imitation learning policies enabling successful performance of dexterous and hard-to-model tasks. Concurrently, scaling data and model size has led to the development of capable language and vision foundation models, motivating large-scale efforts to create general-purpose robot foundation models. Although these models have garnered considerable enthusiasm and investment, meaningful evaluation of real-world performance remains a challenge, limiting the pace of development and inhibiting a nuanced understanding of current capabilities. Here, we rigorously evaluated multitask robot manipulation policies, referred to as large behavior models, by extending the diffusion policy paradigm across a corpus of simulated and real-world robot data. We proposed and validated an evaluation pipeline to rigorously analyze the capabilities of these models with statistical confidence. We compared against single-task baselines through blind, randomized trials in a controlled setting, using both simulation and real-world experiments. We found that multitask pretraining made the policies more successful and robust and enabled teaching complex new tasks more quickly, using a fraction of the data when compared with single-task baselines. Moreover, performance predictably increased as pretraining scale and diversity grows.","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"33 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147681573","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}