Results 101 to 110 of about 2,475,679 (305)

Efficient variational Bayesian model updating by Bayesian active learning

Mechanical Systems and Signal Processing
As a main task of inverse problem, model updating has received more and more attention in the area of inspection, sensing, and monitoring technologies during the recent decades, where the estimation of posterior probability density function (PDF) of unknown model parameters is still challenging for expensive-to-evaluate models of interest.
Fangqi Hong, Pengfei Wei, Sifeng Bi, Michael Beer   +3 more
openaire   +2 more sources

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source

Deep transfer learning with Bayesian optimization for evolutionary-stage prediction of step-like landslides

Frontiers in Earth Science
The landslide displacement in the Three Gorges Reservoir Area (TGRA) follows a step-like pattern, making the evolutionary stage difficult to predict. An optimized transfer learning model integrating a convolutional neural network (CNN) and bidirectional ...
Tao Ma, Huabo Xiao, Yonghang Yang
doaj   +1 more source

On attitude polarization under Bayesian learning with non-additive beliefs [PDF]

Ample psychological evidence suggests that people’s learning behavior is often prone to a "myside bias" or "irrational belief persistence" in contrast to learning behavior exclusively based on objective data.
Alexander Ludwig, Alexander Zimper
core   +1 more source

Enabling Real‐Time Shape‐Sensing in Soft Robots via a Miniaturized, Single‐Signal, Color‐Tuned Soft Optical Sensor

Advanced Robotics Research, EarlyView.
A miniaturized soft optical sensor that uses thin film color tuning enables real‐time 3D shape‐sensing from a single red–green–blue (RGB) signal. When integrated into a soft robot, it enables closed‐loop control and autonomous navigation in a phantom lung environment without the need for onboard electronics, achieving sub‐millimeter accuracy through ...
Frank Juliá Wise, Yitong Lu, Daniel Van Lewen, Riley Applebaum, Bianca Andrada, Johnathan Reamer, Sheila Russo   +6 more
wiley   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion

Advanced Robotics Research, EarlyView.
A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza, Hiroshi Kaminaga, Philippe Fraisse, Gentiane Venture   +3 more
wiley   +1 more source

A Bayesian foundation for individual learning under uncertainty

Frontiers in Human Neuroscience, 2011
Computational learning models are critical for understanding mechanisms of adaptive behavior. However, the two major current frameworks, reinforcement learning (RL) and Bayesian learning, both have certain limitations.
Christoph eMathys, Christoph eMathys, Jean eDaunizeau, Jean eDaunizeau, Karl J Friston, Klaas Enno Stephan, Klaas Enno Stephan   +6 more
doaj   +1 more source

Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re‐Usability: A Position Paper From the Nanosafety Community

Advanced Sustainable Systems, EarlyView.
Nanosafety data provide a guiding example for establishing best practices in data management, aligning with FAIR principles and quality criteria. This review explores existing quality assessment approaches for reliability, relevance, and completeness, emphasizing the need for harmonization and adaptation to nanomaterials and advanced materials. The aim
Verónica I. Dumit, Irini Furxhi, Penny Nymark, Antreas Afantitis, Ammar Ammar, Monica J. B. Amorim, Dalila Antunes, Svetlana Avramova, Chiara L. Battistelli, Gianpietro Basei, Cecilia Bossa, Emil Cimpan, Mihaela Roxana Cimpan, Dmitri Ciornii, Anna Costa, Camilla Delpivo, Maria Dusinska, Ana Sofia Fonseca, Steffi Friedrichs, Vasile‐Dan Hodoroaba, Danail Hristozov, Panagiotis Isigonis, Nina Jeliazkova, Nikolay Kochev, Eva Kranjc, Dieter Maier, Georgia Melagraki, Anastasios G. Papadiamantis, Tomasz Puzyn, Hubert Rauscher, Katie Reilly, Araceli Sánchez Jiménez, Janeck J. Scott‐Fordsmand, Neeraj Shandilya, Hyun Kil Shin, Gergana Tancheva, Jeaphianne P. M. van Rijn, Egon L. Willighagen, Ewelina Wyrzykowska, Martine I. Bakker, Damjana Drobne, Thomas E. Exner, Martin Himly, Iseult Lynch   +43 more
wiley   +1 more source