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Related papers: Robotic Materials

200 papers

Intelligent soft matter stands at the intersection of materials science, physics, and cognitive science, promising to change how we design and interact with materials. This transformative field seeks to create materials that possess…

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many…

Materials Science · Physics 2016-01-12 Rémi Dingreville , Richard A. Karnesky , Guillaume Puel , Jean-Hubert Schmitt

The shift from a linear to a circular economy has the potential to simultaneously reduce uncertainties of material supplies and waste generation. However, to date, the development of robotic and, more generally, autonomous systems have been…

Robotics · Computer Science 2024-11-28 Federico Zocco , Wassim M. Haddad , Andrea Corti , Monica Malvezzi

This paper reviews machine learning applications and approaches to detection, classification and control of intelligent materials and structures with embedded distributed computation elements. The purpose of this survey is to identify…

Machine Learning · Computer Science 2016-06-14 Dana Hughes , Nikolaus Correll

We present recommendations to improve reproducibility and replicability in condensed matter physics. This area of physics has consistently produced both fundamental insights into the workings of matter and transformative inventions. Our…

A key challenge in intelligent robotics is creating robots that are capable of directly interacting with the world around them to achieve their goals. The last decade has seen substantial growth in research on the problem of robot…

Robotics · Computer Science 2020-11-10 Oliver Kroemer , Scott Niekum , George Konidaris

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming…

Quantum Physics · Physics 2024-09-20 Yuri Alexeev , Maximilian Amsler , Paul Baity , Marco Antonio Barroca , Sanzio Bassini , Torey Battelle , Daan Camps , David Casanova , Young Jai Choi , Frederic T. Chong , Charles Chung , Chris Codella , Antonio D. Corcoles , James Cruise , Alberto Di Meglio , Jonathan Dubois , Ivan Duran , Thomas Eckl , Sophia Economou , Stephan Eidenbenz , Bruce Elmegreen , Clyde Fare , Ismael Faro , Cristina Sanz Fernández , Rodrigo Neumann Barros Ferreira , Keisuke Fuji , Bryce Fuller , Laura Gagliardi , Giulia Galli , Jennifer R. Glick , Isacco Gobbi , Pranav Gokhale , Salvador de la Puente Gonzalez , Johannes Greiner , Bill Gropp , Michele Grossi , Emanuel Gull , Burns Healy , Benchen Huang , Travis S. Humble , Nobuyasu Ito , Artur F. Izmaylov , Ali Javadi-Abhari , Douglas Jennewein , Shantenu Jha , Liang Jiang , Barbara Jones , Wibe Albert de Jong , Petar Jurcevic , William Kirby , Stefan Kister , Masahiro Kitagawa , Joel Klassen , Katherine Klymko , Kwangwon Koh , Masaaki Kondo , Doga Murat Kurkcuoglu , Krzysztof Kurowski , Teodoro Laino , Ryan Landfield , Matt Leininger , Vicente Leyton-Ortega , Ang Li , Meifeng Lin , Junyu Liu , Nicolas Lorente , Andre Luckow , Simon Martiel , Francisco Martin-Fernandez , Margaret Martonosi , Claire Marvinney , Arcesio Castaneda Medina , Dirk Merten , Antonio Mezzacapo , Kristel Michielsen , Abhishek Mitra , Tushar Mittal , Kyungsun Moon , Joel Moore , Mario Motta , Young-Hye Na , Yunseong Nam , Prineha Narang , Yu-ya Ohnishi , Daniele Ottaviani , Matthew Otten , Scott Pakin , Vincent R. Pascuzzi , Ed Penault , Tomasz Piontek , Jed Pitera , Patrick Rall , Gokul Subramanian Ravi , Niall Robertson , Matteo Rossi , Piotr Rydlichowski , Hoon Ryu , Georgy Samsonidze , Mitsuhisa Sato , Nishant Saurabh , Vidushi Sharma , Kunal Sharma , Soyoung Shin , George Slessman , Mathias Steiner , Iskandar Sitdikov , In-Saeng Suh , Eric Switzer , Wei Tang , Joel Thompson , Synge Todo , Minh Tran , Dimitar Trenev , Christian Trott , Huan-Hsin Tseng , Esin Tureci , David García Valinas , Sofia Vallecorsa , Christopher Wever , Konrad Wojciechowski , Xiaodi Wu , Shinjae Yoo , Nobuyuki Yoshioka , Victor Wen-zhe Yu , Seiji Yunoki , Sergiy Zhuk , Dmitry Zubarev

Quantum materials exhibit a wide array of exotic phenomena and practically useful properties. A better understanding of these materials can provide deeper insights into fundamental physics in the quantum realm as well as advance technology…

The convergence of artificial intelligence and materials science presents a transformative opportunity, but achieving true acceleration in discovery requires moving beyond task-isolated, fine-tuned models toward agentic systems that plan,…

With the transformative technologies and the rapidly changing global R&D landscape, the multimedia and multimodal community is now faced with many new opportunities and uncertainties. With the open source dissemination platform and…

Significant progress in robotics reveals new opportunities to advance manufacturing. Next-generation industrial automation will require both integration of distinct robotic technologies and their application to challenging industrial…

High-throughput data generation methods and machine learning (ML) algorithms have given rise to a new era of computational materials science by learning relationships among composition, structure, and properties and by exploiting such…

Randomized algorithms have propelled advances in artificial intelligence and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science,…

Propelled partly by the Materials Genome Initiative, and partly by the algorithmic developments and the resounding successes of data-driven efforts in other domains, informatics strategies are beginning to take shape within materials…

Materials Science · Physics 2017-07-25 Rampi Ramprasad , Rohit Batra , Ghanshyam Pilania , Arun Mannodi-Kanakkithodi , Chiho Kim

The National Robotics Initiative (NRI) was launched 2011 and is about to celebrate its 5 year anniversary. In parallel with the NRI, the robotics community, with support from the Computing Community Consortium, engaged in a series of road…

Computers and Society · Computer Science 2016-06-30 Henrik I Christensen , Allison Okamura , Maja Mataric , Vijay Kumar , Greg Hager , Howie Choset

Recently there has been an ever-increasing trend in the use of machine learning (ML) and artificial intelligence (AI) methods by the materials science, condensed matter physics, and chemistry communities. This perspective article identifies…

Materials Science · Physics 2020-03-20 Brian DeCost , Jason Hattrick-Simpers , Zachary Trautt , Aaron Kusne , Eva Campo , Martin Green

The design of intelligent materials often draws parallels with the complex adaptive behaviors of biological organisms, where robust functionality stems from sophisticated hierarchical organization and emergent long-distance coordination…

Soft Condensed Matter · Physics 2025-11-13 Vladimir A. Baulin , Rudolf M. Füchslin , Achille Giacometti , Helmut Hauser , Marco Werner

Recent advancements in robotics have transformed industries such as manufacturing, logistics, surgery, and planetary exploration. A key challenge is developing efficient motion planning algorithms that allow robots to navigate complex…

Robotics · Computer Science 2025-08-27 Liding Zhang , Kuanqi Cai , Zewei Sun , Zhenshan Bing , Chaoqun Wang , Luis Figueredo , Sami Haddadin , Alois Knoll

Active matter physics and swarm robotics have provided powerful tools for the study and control of ensembles driven by internal sources. At the macroscale, controlling swarms typically utilizes significant memory, processing power, and…