Science Robotics最新文献_第3页

Robots and animals teaming up in the wild to tackle ecosystem challenges 机器人和动物在野外联手应对生态系统的挑战。

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-11-20 DOI: 10.1126/scirobotics.ado5566

Thomas Schmickl, Donato Romano

引用次数: 0

Bird-inspired reflexive morphing enables rudderless flight 受鸟类启发的反射变形实现了无舵飞行

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-11-20 DOI: 10.1126/scirobotics.ado4535

Eric Chang, Diana D. Chin, David Lentink

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引用次数: 0

NeuralFeels with neural fields: Visuotactile perception for in-hand manipulation 神经感觉与神经场手部操作的视觉触觉感知

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-11-13 DOI: 10.1126/scirobotics.adl0628

Sudharshan Suresh, Haozhi Qi, Tingfan Wu, Taosha Fan, Luis Pineda, Mike Lambeta, Jitendra Malik, Mrinal Kalakrishnan, Roberto Calandra, Michael Kaess, Joseph Ortiz, Mustafa Mukadam

{"title":"NeuralFeels with neural fields: Visuotactile perception for in-hand manipulation","authors":"Sudharshan Suresh, Haozhi Qi, Tingfan Wu, Taosha Fan, Luis Pineda, Mike Lambeta, Jitendra Malik, Mrinal Kalakrishnan, Roberto Calandra, Michael Kaess, Joseph Ortiz, Mustafa Mukadam","doi":"10.1126/scirobotics.adl0628","DOIUrl":"10.1126/scirobotics.adl0628","url":null,"abstract":"<div >To achieve human-level dexterity, robots must infer spatial awareness from multimodal sensing to reason over contact interactions. During in-hand manipulation of novel objects, such spatial awareness involves estimating the object’s pose and shape. The status quo for in-hand perception primarily uses vision and is restricted to tracking a priori known objects. Moreover, visual occlusion of objects in hand is imminent during manipulation, preventing current systems from pushing beyond tasks without occlusion. We combined vision and touch sensing on a multifingered hand to estimate an object’s pose and shape during in-hand manipulation. Our method, NeuralFeels, encodes object geometry by learning a neural field online and jointly tracks it by optimizing a pose graph problem. We studied multimodal in-hand perception in simulation and the real world, interacting with different objects via a proprioception-driven policy. Our experiments showed final reconstruction <i>F</i> scores of 81% and average pose drifts of 4.7 millimeters, which was further reduced to 2.3 millimeters with known object models. In addition, we observed that, under heavy visual occlusion, we could achieve improvements in tracking up to 94% compared with vision-only methods. Our results demonstrate that touch, at the very least, refines and, at the very best, disambiguates visual estimates during in-hand manipulation. We release our evaluation dataset of 70 experiments, FeelSight, as a step toward benchmarking in this domain. Our neural representation driven by multimodal sensing can serve as a perception backbone toward advancing robot dexterity.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 96","pages":""},"PeriodicalIF":26.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.science.org/doi/reader/10.1126/scirobotics.adl0628","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142601978","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}

引用次数: 0

Crucial hurdles to achieving human-robot harmony 实现人与机器人和谐相处的关键障碍。

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-11-13 DOI: 10.1126/scirobotics.adp2507

Keya Ghonasgi, Taylor Higgins, Meghan E. Huber, Marcia K. O’Malley

引用次数: 0

How much initiative should a service robot have? 服务机器人应该有多少主动权？

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-11-13 DOI: 10.1126/scirobotics.adt8902

Robin R. Murphy

引用次数: 0

Self-organizing nervous systems for robot swarms 机器人群的自组织神经系统

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-11-13 DOI: 10.1126/scirobotics.adl5161

Weixu Zhu, Sinan Oğuz, Mary Katherine Heinrich, Michael Allwright, Mostafa Wahby, Anders Lyhne Christensen, Emanuele Garone, Marco Dorigo

{"title":"Self-organizing nervous systems for robot swarms","authors":"Weixu Zhu, Sinan Oğuz, Mary Katherine Heinrich, Michael Allwright, Mostafa Wahby, Anders Lyhne Christensen, Emanuele Garone, Marco Dorigo","doi":"10.1126/scirobotics.adl5161","DOIUrl":"10.1126/scirobotics.adl5161","url":null,"abstract":"<div >We present the self-organizing nervous system (SoNS), a robot swarm architecture based on self-organized hierarchy. The SoNS approach enables robots to autonomously establish, maintain, and reconfigure dynamic multilevel system architectures. For example, a robot swarm consisting of <i>n</i> independent robots could transform into a single <i>n</i>–robot SoNS and then into several independent smaller SoNSs, where each SoNS uses a temporary and dynamic hierarchy. Leveraging the SoNS approach, we showed that sensing, actuation, and decision-making can be coordinated in a locally centralized way without sacrificing the benefits of scalability, flexibility, and fault tolerance, for which swarm robotics is usually studied. In several proof-of-concept robot missions—including binary decision-making and search and rescue—we demonstrated that the capabilities of the SoNS approach greatly advance the state of the art in swarm robotics. The missions were conducted with a real heterogeneous aerial-ground robot swarm, using a custom-developed quadrotor platform. We also demonstrated the scalability of the SoNS approach in swarms of up to 250 robots in a physics-based simulator and demonstrated several types of system fault tolerance in simulation and reality.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 96","pages":""},"PeriodicalIF":26.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.science.org/doi/reader/10.1126/scirobotics.adl5161","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142602028","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}

引用次数: 0

Advancing scientific discovery with the aid of robotics. 借助机器人技术推动科学发现。

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-10-30 DOI: 10.1126/scirobotics.adt3842

Amos Matsiko

引用次数: 0

Understanding the sense of self through robotics. 通过机器人了解自我意识。

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-10-30 DOI: 10.1126/scirobotics.adn2733

Tony J Prescott, Kai Vogeley, Agnieszka Wykowska

引用次数: 0

Reinforcement learning-based framework for whale rendezvous via autonomous sensing robots. 基于强化学习的自主感知机器人鲸鱼会合框架。

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-10-30 DOI: 10.1126/scirobotics.adn7299

Ninad Jadhav, Sushmita Bhattacharya, Daniel Vogt, Yaniv Aluma, Pernille Tønnesen, Akarsh Prabhakara, Swarun Kumar, Shane Gero, Robert J Wood, Stephanie Gil

{"title":"Reinforcement learning-based framework for whale rendezvous via autonomous sensing robots.","authors":"Ninad Jadhav, Sushmita Bhattacharya, Daniel Vogt, Yaniv Aluma, Pernille Tønnesen, Akarsh Prabhakara, Swarun Kumar, Shane Gero, Robert J Wood, Stephanie Gil","doi":"10.1126/scirobotics.adn7299","DOIUrl":"10.1126/scirobotics.adn7299","url":null,"abstract":"<p><p>Rendezvous with sperm whales for biological observations is made challenging by their prolonged dive patterns. Here, we propose an algorithmic framework that codevelops multiagent reinforcement learning-based routing (autonomy module) and synthetic aperture radar-based very high frequency (VHF) signal-based bearing estimation (sensing module) for maximizing rendezvous opportunities of autonomous robots with sperm whales. The sensing module is compatible with low-energy VHF tags commonly used for tracking wildlife. The autonomy module leverages in situ noisy bearing measurements of whale vocalizations, VHF tags, and whale dive behaviors to enable time-critical rendezvous of a robot team with multiple whales in simulation. We conducted experiments at sea in the native habitat of sperm whales using an \"engineered whale\"-a speedboat equipped with a VHF-emitting tag, emulating five distinct whale tracks, with different whale motions. The sensing module shows a median bearing error of 10.55° to the tag. Using bearing measurements to the engineered whale from an acoustic sensor and our sensing module, our autonomy module gives an aggregate rendezvous success rate of 81.31% for a 500-meter rendezvous distance using three robots in postprocessing. A second class of fielded experiments that used acoustic-only bearing measurements to three untagged sperm whales showed an aggregate rendezvous success rate of 68.68% for a 1000-meter rendezvous distance using two robots in postprocessing. We further validated these algorithms with several ablation studies using a sperm whale visual encounter dataset collected by marine biologists.</p>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 95","pages":"eadn7299"},"PeriodicalIF":26.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142549175","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

Augmented dexterity: How robots can enhance human surgical skills 增强灵巧性：机器人如何提高人类的外科手术技能。

IF 26.1 1区计算机科学

Science Robotics Pub Date : 2024-10-30 DOI: 10.1126/scirobotics.adr5247

Ken Goldberg, Gary Guthart

引用次数: 0