Results 201 to 210 of about 10,882 (268)

3D‐Nanoprinted Fluidically Steerable Soft Robotic Microcatheters

Advanced Robotics Research, EarlyView.
This work introduces a ∼3‐French (1 mm‐in‐diameter) soft robotic microcatheter fabricated by means of two‐photon direct laser writing. The 3D‐printed microcatheter enables remote, on‐demand steering via microfluidic actuation for guidewire‐free navigation of vascular networks as well as microcatheter‐mediated delivery of fluidic payloads to target ...
Bailey M. Felix, Molly Carton, Olivia M. Young, Noah Barnes, Jordi T. Andreou, Sarah McHugh, Jack E. McCann, Claudia Davis, Victoria Reddig‐Leiman, Afsah Kamran, Dheeraj Gandhi, Miroslaw Janowski, Jeremy D. Brown, Mark Fuge, Axel Krieger, Clifford R. Weiss, Christopher R. Bailey, Ryan D. Sochol   +17 more
wiley   +1 more source

Reliable parameter estimation of nonlinear chaotic systems and PMSMs with the stellar oscillation optimizer. [PDF]

Sci Rep
Ekinci S, Izci D, Jabari M, Elsayed F, Salman M, Bektaş Güneş B.   +5 more
europepmc   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Data-driven acceleration of mixed-integer bilinear programs: a comparative study for robot motion planning. [PDF]

Front Robot AI
Lin X.
europepmc   +1 more source

Functional Fibers in Soft Robotics: Advances in Material, Structural, and Systemic Tactics

Advanced Robotics Research, EarlyView.
Fiber‐form robotic systems offer a scalable pathway toward embodied intelligence in soft robotics. This review surveys functional fibers as material, structural, and systemic elements, highlighting advances in responsive materials, architectural programing, and fabrication strategies.
Joonhee Won, Jaehyun Jang, Hyeonseo Kim, Inyoung Choi, Steve Park, Seongjun Park   +5 more
wiley   +1 more source

Fractional-order epidemic modeling with a deep neural network framework. [PDF]

Sci Rep
Jangir P, Agarwal G, Nisar KS.
europepmc   +1 more source

Autonomous Navigation of Pollen‐Inspired Magnetic Microrobots for Biomedical Applications

Advanced Robotics Research, EarlyView.
A sunflower pollen‐inspired magnetic microrobot enables controlled rolling navigation in vessel‐like environments. Its open geometry reduces hydrodynamic drag, while vision‐based closed‐loop control, shortest‐path planning, and reinforcement learning support target‐reaching and maze navigation with microrobot‐scale accuracy, highlighting a route toward
Ali Anil Demircali, Abdurrahim Yilmaz, Meysam Keshavarz, Jinshi Zhao, Ara Darzi, Eric Yeatman, Burak Temelkuran   +6 more
wiley   +1 more source

Stochastic optimization framework for microgrid energy management integrating electric vehicles, renewable sources, and storage. [PDF]

Sci Rep
Ali ZM, Mostafa MH.
europepmc   +1 more source

Helix Alignment, Chevrons, and Edge Dislocations in Twist‐Bend Ferroelectric Nematics

Advanced Science, EarlyView.
The recently discovered twist‐bend ferroelectric nematic (NTBF) is the new member of the multiferroic family, representing a fluid with an oblique helicoidal (heliconical) periodic structure of spontaneous electric polarization. The work presents a thorough exploration of the material properties of this phase, how the periodic modulation of ...
Bijaya Basnet, Priyanka Kumari, Sathyanarayana Paladugu, Damian Pociecha, Jakub Karcz, Przemysław Kula, Nataša Vaupotič, Ewa Górecka, Oleg D Lavrentovich   +8 more
wiley   +1 more source

Comparative evaluation of machine learning and deep learning approaches for compressive strength prediction of geopolymer concrete. [PDF]

Sci Rep
Ezz H, Bakr SM.
europepmc   +1 more source