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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 Q1 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

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.

与抹香鲸会合进行生物观测因其长时间的潜水模式而具有挑战性。在此,我们提出了一个算法框架,该框架开发了基于多代理强化学习的路由选择(自主模块)和基于合成孔径雷达甚高频(VHF)信号的方位估计(传感模块),以最大限度地提高自主机器人与抹香鲸会合的机会。传感模块与常用于追踪野生动物的低能耗甚高频标签兼容。自主模块利用对鲸鱼发声、甚高频标签和鲸鱼潜水行为的现场噪声方位测量,在模拟中实现机器人团队与多头鲸鱼的时间关键性会合。我们在抹香鲸的原生栖息地进行了海上实验,使用了 "工程鲸"--一艘装有甚高频发射标签的快艇,模拟了五种不同的鲸鱼运动轨迹。传感模块与标签的中位方位误差为 10.55°。利用声学传感器和传感模块对工程鲸的方位测量,我们的自主模块在后处理中使用三个机器人在 500 米交会距离内的总交会成功率为 81.31%。第二类实地实验使用声学方位测量法测量了三头未标记抹香鲸的方位,结果显示,使用两个机器人进行后处理,在 1000 米交会距离上的总交会成功率为 68.68%。我们还利用海洋生物学家收集的抹香鲸目视相遇数据集进行了多项消融研究,进一步验证了这些算法。
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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 Q1 ROBOTICS Pub Date : 2024-10-30 DOI: 10.1126/scirobotics.adn2733
Tony J Prescott, Kai Vogeley, Agnieszka Wykowska

Robotics can play a useful role in the scientific understanding of the sense of self, both through the construction of embodied models of the self and through the use of robots as experimental probes to explore the human self. In both cases, the embodiment of the robot allows us to devise and test hypotheses about the nature of the self, with regard to its development, its manifestation in behavior, and the diversity of selves in humans, animals, and, potentially, machines. This paper reviews robotics research that addresses the topic of the self-the minimal self, the extended self, and disorders of the self-and highlights future directions and open challenges in understanding the self through constructing its components in artificial systems. An emerging view is that key phenomena of the self can be generated in robots with suitably configured sensor and actuator systems and a layered cognitive architecture involving networks of predictive models.

机器人技术可以在科学理解自我意识方面发挥有益的作用,既可以通过构建自我的具身模型,也可以通过使用机器人作为探索人类自我的实验探针。在这两种情况下,机器人的化身都能让我们设计和测试有关自我本质的假设,包括自我的发展、自我在行为中的表现,以及人类、动物和潜在机器中自我的多样性。本文回顾了涉及自我主题的机器人研究--最小自我、扩展自我和自我失调,并强调了通过在人工系统中构建自我的组成部分来理解自我的未来方向和挑战。一种新出现的观点认为,通过适当配置传感器和执行器系统以及涉及预测模型网络的分层认知架构,可以在机器人中生成自我的关键现象。
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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 Q1 ROBOTICS Pub Date : 2024-10-30 DOI: 10.1126/scirobotics.adr5247
Ken Goldberg, Gary Guthart
Advances in AI and robotics have the potential to enhance the dexterity of human surgeons.
人工智能和机器人技术的进步有可能提高人类外科医生的灵巧性。
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引用次数: 0
AI-driven aerial robots advance whale research. 人工智能驱动的空中机器人推进鲸鱼研究。
IF 26.1 1区 计算机科学 Q1 ROBOTICS Pub Date : 2024-10-30 DOI: 10.1126/scirobotics.adt1955
Haluk Bayram

Aerial robots assisted with artificial intelligence improve real-time wildlife monitoring of sperm whales.

人工智能辅助的空中机器人改善了对抹香鲸的实时野生动物监测。
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引用次数: 0
Transforming science labs into automated factories of discovery 将科学实验室改造成自动化发现工厂
IF 25 1区 计算机科学 Q1 ROBOTICS Pub Date : 2024-10-23 DOI: 10.1126/scirobotics.adm6991
Angelos Angelopoulos, James F. Cahoon, Ron Alterovitz
Laboratories in chemistry, biochemistry, and materials science are at the leading edge of technology, discovering molecules and materials to unlock capabilities in energy, catalysis, biotechnology, sustainability, electronics, and more. Yet, most modern laboratories resemble factories from generations past, with a large reliance on humans manually performing synthesis and characterization tasks. Robotics and automation can enable scientific experiments to be conducted faster, more safely, more accurately, and with greater reproducibility, allowing scientists to tackle large societal problems in domains such as health and energy on a shorter timescale. We define five levels of laboratory automation, from laboratory assistance to full automation. We also introduce robotics research challenges that arise when increasing levels of automation and when increasing the generality of tasks within the laboratory. Robots are poised to transform science labs into automated factories of discovery that accelerate scientific progress.
化学、生物化学和材料科学实验室处于技术的前沿,它们发现的分子和材料能够开启能源、催化、生物技术、可持续发展、电子等领域的能力。然而,大多数现代实验室与过去的工厂相似,主要依靠人类手动完成合成和表征任务。机器人技术和自动化可使科学实验更快、更安全、更准确地进行,并具有更高的可重复性,从而使科学家能够在更短的时间内解决健康和能源等领域的重大社会问题。我们定义了实验室自动化的五个级别,从实验室辅助到完全自动化。我们还介绍了在提高自动化水平和增加实验室内任务的通用性时出现的机器人研究挑战。机器人有望将科学实验室转变为加速科学进步的自动化发现工厂。
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引用次数: 0
Ted Chiang imagines a computational theory of robots 特德-蒋(Ted Chiang)设想了一种机器人计算理论。
IF 26.1 1区 计算机科学 Q1 ROBOTICS Pub Date : 2024-10-23 DOI: 10.1126/scirobotics.adt3828
Robin R. Murphy
Two short science fiction stories, “Exhalation” and “Seventy-Two Letters”, explore robots inside and out.
两篇科幻短篇小说《呼气》和《七十二封信》探讨了机器人的内在和外在。
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引用次数: 0
Paleoinspired robotics as an experimental approach to the history of life 受古生物启发的机器人技术是研究生命史的一种实验方法
IF 25 1区 计算机科学 Q1 ROBOTICS Pub Date : 2024-10-23 DOI: 10.1126/scirobotics.adn1125
Michael Ishida, Fidji Berio, Valentina Di Santo, Neil H. Shubin, Fumiya Iida
Paleontologists must confront the challenge of studying the forms and functions of extinct species for which data from preserved fossils are extremely limited, yielding only a fragmented picture of life in deep time. In response to this hurdle, we describe the nascent field of paleoinspired robotics, an innovative method that builds upon established techniques in bioinspired robotics, enabling the exploration of the biology of ancient organisms and their evolutionary trajectories. This Review presents ways in which robotic platforms can fill gaps in existing research using the exemplars of notable transitions in vertebrate locomotion. We examine recent case studies in experimental paleontology, highlighting substantial contributions made by engineering and robotics techniques, and further assess how the efficient application of robotic technologies in close collaboration with paleontologists and biologists can offer additional insights into the study of evolution that were previously unattainable.
古生物学家必须面对研究已灭绝物种的形态和功能这一挑战,因为从保存下来的化石中获得的数据极为有限,只能获得深部生命的片段图景。为了应对这一挑战,我们介绍了古生物启发机器人学这一新兴领域,这是一种建立在生物启发机器人学已有技术基础上的创新方法,能够探索古生物的生物学特性及其进化轨迹。本综述以脊椎动物运动的显著转变为例,介绍了机器人平台填补现有研究空白的方法。我们研究了最近在实验古生物学方面的案例研究,强调了工程学和机器人技术所做出的重大贡献,并进一步评估了如何通过与古生物学家和生物学家密切合作,有效地应用机器人技术,为进化研究提供更多以前无法获得的见解。
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引用次数: 0
Robotic manipulation of cardiomyocytes to identify gap junction modifiers for arrhythmogenic cardiomyopathy 用机器人操纵心肌细胞识别心律失常性心肌病的间隙连接修饰因子
IF 25 1区 计算机科学 Q1 ROBOTICS Pub Date : 2024-10-23 DOI: 10.1126/scirobotics.adm8233
Wenkun Dou, Guanqiao Shan, Qili Zhao, Manpreet Malhi, Aojun Jiang, Zhuoran Zhang, Andrés González-Guerra, Shaojie Fu, Junhui Law, Robert M. Hamilton, Juan A. Bernal, Xinyu Liu, Yu Sun, Jason T. Maynes
Arrhythmogenic cardiomyopathy (ACM) is a leading cause of sudden cardiac death among young adults. Aberrant gap junction remodeling has been linked to disease-causative mutations in plakophilin-2 ( PKP2 ). Although gap junctions are a key therapeutic target, measurement of gap junction function in preclinical disease models is technically challenging. To quantify gap junction function with high precision and high consistency, we developed a robotic cell manipulation system with visual feedback from digital holographic microscopy for three-dimensional and label-free imaging of human induced pluripotent stem cell–derived cardiomyocytes (iPSC-CMs). The robotic system can accurately determine the dynamic height changes in the cells’ contraction and resting phases, microinject drug-treated healthy and diseased iPSC-CMs in their resting phase with constant injection depth across all cells, and deposit a membrane-impermeable dye that solely diffuses between cells through gap junctions for measuring the gap junction diffusion function. The robotic system was applied toward a targeted drug screen to identify gap junction modulators and potential therapeutics for ACM. Five compounds were found to dose-dependently enhance gap junction permeability in cardiomyocytes with PKP2 knockdown. In addition, PCO 400 (pinacidil) reduced beating irregularity in a mouse model of ACM expressing mutant PKP2 (R735X). These results highlight the utility of the robotic cell manipulation system to efficiently assess gap junction function in a relevant preclinical disease model, thus providing a technique to advance drug discovery for ACM and other gap junction–mediated diseases.
心律失常性心肌病(ACM)是青壮年心脏性猝死的主要原因。间隙连接重塑异常与 plakophilin-2 (PKP2)的致病突变有关。虽然间隙连接是一个关键的治疗靶点,但在临床前疾病模型中测量间隙连接的功能在技术上具有挑战性。为了高精度、高一致性地量化间隙连接功能,我们开发了一种机器人细胞操纵系统,该系统利用数字全息显微镜的视觉反馈,对人类诱导多能干细胞衍生的心肌细胞(iPSC-CMs)进行三维无标记成像。该机器人系统能准确测定细胞收缩期和静息期的动态高度变化,以恒定的注射深度对静息期的健康和患病 iPSC-CMs 进行显微注射,并沉积仅通过间隙连接在细胞间扩散的膜渗透性染料,以测量间隙连接扩散功能。该机器人系统被用于靶向药物筛选,以确定间隙连接调节剂和治疗 ACM 的潜在疗法。结果发现,在 PKP2 被敲除的心肌细胞中,有五种化合物能按剂量依赖性地增强缝隙连接的通透性。此外,在表达突变型 PKP2(R735X)的 ACM 小鼠模型中,PCO 400(pinacidil)减少了跳动不规则性。这些结果凸显了机器人细胞操纵系统在相关临床前疾病模型中有效评估间隙连接功能的实用性,从而为推动治疗 ACM 和其他间隙连接介导疾病的药物发现提供了一种技术。
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引用次数: 0
High-tech guardians: Robotics at the heart of the Future Circular Collider. 高科技守护者:机器人技术是未来环形对撞机的核心。
IF 25 1区 计算机科学 Q1 ROBOTICS Pub Date : 2024-10-16 DOI: 10.1126/scirobotics.adm7965
Hannes Gamper,Andreas Mueller,Mario Di Castro
A holistic robotic concept for inspection, maintenance, and emergency interventions for the Future Circular Collider is presented.
介绍了用于未来环形对撞机的检查、维护和紧急干预的整体机器人概念。
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引用次数: 0
Autonomous tracking of honey bee behaviors over long-term periods with cooperating robots 利用合作机器人长期自主跟踪蜜蜂行为
IF 25 1区 计算机科学 Q1 ROBOTICS Pub Date : 2024-10-16 DOI: 10.1126/scirobotics.adn6848
Jiří Ulrich, Martin Stefanec, Fatemeh Rekabi-Bana, Laurenz Alexander Fedotoff, Tomáš Rouček, Bilal Yağız Gündeğer, Mahmood Saadat, Jan Blaha, Jiří Janota, Daniel Nicolas Hofstadler, Kristina Žampachů, Erhan Ege Keyvan, Babür Erdem, Erol Şahin, Hande Alemdar, Ali Emre Turgut, Farshad Arvin, Thomas Schmickl, Tomáš Krajník
Digital and mechatronic methods, paired with artificial intelligence and machine learning, are transformative technologies in behavioral science and biology. The central element of the most important pollinator species—honey bees—is the colony’s queen. Because honey bee self-regulation is complex and studying queens in their natural colony context is difficult, the behavioral strategies of these organisms have not been widely studied. We created an autonomous robotic observation and behavioral analysis system aimed at continuous observation of the queen and her interactions with worker bees and comb cells, generating behavioral datasets of exceptional length and quality. Key behavioral metrics of the queen and her social embedding within the colony were gathered using our robotic system. Data were collected continuously for 24 hours a day over a period of 30 days, demonstrating our system’s capability to extract key behavioral metrics at microscopic, mesoscopic, and macroscopic system levels. Additionally, interactions among the queen, worker bees, and brood were observed and quantified. Long-term continuous observations performed by the robot yielded large amounts of high-definition video data that are beyond the observation capabilities of humans or stationary cameras. Our robotic system can enable a deeper understanding of the innermost mechanisms of honey bees’ swarm-intelligent self-regulation. Moreover, it offers the possibility to study other social insect colonies, biocoenoses, and ecosystems in an automated manner. Social insects are keystone species in all terrestrial ecosystems; thus, developing a better understanding of their behaviors will be invaluable for the protection and even the restoration of our fragile ecosystems globally.
数字化和机电一体化方法与人工智能和机器学习相结合,是行为科学和生物学领域的变革性技术。最重要的授粉物种--蜜蜂--的核心要素是蜂群的蜂王。由于蜜蜂的自我调节非常复杂,而且在自然蜂群环境中研究蜂王非常困难,因此这些生物的行为策略尚未得到广泛研究。我们创建了一个自主机器人观察和行为分析系统,旨在对蜂王及其与工蜂和蜂巢细胞的互动进行持续观察,从而生成长度和质量都非常高的行为数据集。我们的机器人系统收集了蜂王的关键行为指标及其在蜂群中的社会嵌入情况。在 30 天的时间里,我们每天 24 小时不间断地收集数据,证明了我们的系统有能力提取微观、中观和宏观系统层面的关键行为指标。此外,还对蜂王、工蜂和雏蜂之间的互动进行了观察和量化。机器人进行的长期连续观测产生了大量高清视频数据,这是人类或固定摄像机无法观测到的。我们的机器人系统可以让人们更深入地了解蜜蜂蜂群智能自我调节的内在机制。此外,它还为以自动化方式研究其他社会性昆虫群落、生物群落和生态系统提供了可能。社会性昆虫是所有陆地生态系统中的关键物种;因此,更好地了解它们的行为对于保护甚至恢复全球脆弱的生态系统将是非常有价值的。
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引用次数: 0
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Science Robotics
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