2020 - Fellow of the American Association for the Advancement of Science (AAAS)
2017 - Fellow of the American Academy of Arts and Sciences
2015 - Member of the National Academy of Engineering For contributions to distributed robotic systems.
2014 - ACM Fellow For contributions to robotics and sensor networks.
2010 - IEEE Fellow For contributions to distributed and modular robotics
2009 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the theory and practice of distributed robotics, agents, and sensor networks.
2002 - Fellow of the MacArthur Foundation
1998 - Fellow of Alfred P. Sloan Foundation
Her main research concerns Robot, Mobile robot, Artificial intelligence, Wireless sensor network and Control engineering. She does research in Robot, focusing on Robot control specifically. Her biological study deals with issues like Task, which deal with fields such as State.
In her study, Social robot is inextricably linked to Computer vision, which falls within the broad field of Artificial intelligence. The various areas that she examines in her Wireless sensor network study include Node, Key distribution in wireless sensor networks, Real-time computing and Distributed computing. Her study explores the link between Control engineering and topics such as Robotic systems that cross with problems in Mechanism.
Her primary areas of investigation include Robot, Artificial intelligence, Mobile robot, Control engineering and Distributed computing. Her Robot research includes elements of Simulation, Control theory and Modular design. Her Artificial intelligence study combines topics in areas such as Machine learning, Task and Computer vision.
The study incorporates disciplines such as Control theory and Human–computer interaction in addition to Mobile robot. Her Control engineering study frequently draws connections to other fields, such as Actuator. In her research on the topic of Distributed computing, Key distribution in wireless sensor networks is strongly related with Wireless sensor network.
Daniela Rus mainly investigates Artificial intelligence, Robot, Soft robotics, Computer vision and Trajectory. Her Artificial intelligence research focuses on subjects like Machine learning, which are linked to Task, Workflow, Laparoscopic cholecystectomy and Code. Her Robot research integrates issues from Control engineering, Control theory, Control theory and Modular design.
Daniela Rus interconnects Grippers, Curvature and Simulation in the investigation of issues within Soft robotics. The Computer vision study combines topics in areas such as Function and Lidar. Her work is dedicated to discovering how Lidar, Inertial measurement unit are connected with Real-time computing and other disciplines.
Her scientific interests lie mostly in Robot, Artificial intelligence, Soft robotics, Computer vision and Artificial neural network. Her studies deal with areas such as Control engineering, Control theory, Task and Constant curvature as well as Robot. Her Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Scalability.
Her studies in Soft robotics integrate themes in fields like Grippers, Curvature and Simulation. The Smoothing research she does as part of her general Computer vision study is frequently linked to other disciplines of science, such as Extramural, Laparoscopic sleeve gastrectomy and Observer variation, therefore creating a link between diverse domains of science. Her Artificial neural network research includes themes of Subnetwork, Inference, Filter, Algorithm and Convolutional neural network.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Design, fabrication and control of soft robots
Daniela Rus;Michael T. Tolley.
Nature (2015)
Robust distributed network localization with noisy range measurements
David Moore;John Leonard;Daniela Rus;Seth Teller.
international conference on embedded networked sensor systems (2004)
Modular Self-Reconfigurable Robot Systems [Grand Challenges of Robotics]
M. Yim;Wei-Min Shen;B. Salemi;D. Rus.
IEEE Robotics & Automation Magazine (2007)
Data collection, storage, and retrieval with an underwater sensor network
I. Vasilescu;K. Kotay;D. Rus;M. Dunbabin.
international conference on embedded networked sensor systems (2005)
Global clock synchronization in sensor networks
Qun Li;D. Rus.
IEEE Transactions on Computers (2006)
Online power-aware routing in wireless Ad-hoc networks
Qun Li;Javed Aslam;Daniela Rus.
acm/ieee international conference on mobile computing and networking (2001)
A method for building self-folding machines
S. Felton;M. Tolley;E. Demaine;D. Rus.
Science (2014)
Programmable matter by folding
E. Hawkes;B. An;N. M. Benbernou;H. Tanaka.
Proceedings of the National Academy of Sciences of the United States of America (2010)
Tracking a moving object with a binary sensor network
Javed Aslam;Zack Butler;Florin Constantin;Valentino Crespi.
international conference on embedded networked sensor systems (2003)
Autonomous Soft Robotic Fish Capable of Escape Maneuvers Using Fluidic Elastomer Actuators.
Andrew D. Marchese;Cagdas D. Onal;Daniela Rus.
Soft robotics (2014)
Profile was last updated on December 6th, 2021.
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