Results 161 to 170 of about 42,816 (266)

In Situ Integrated Titanium Oxide Synaptic Phototransistor Enabling Multimodal Plasticity and Noise‐Robust Selective Attention

Advanced Materials Technologies, EarlyView.
An in situ integrated TiO2/SiOx/Al2O3 synaptic phototransistor couples ultraviolet and electrical stimuli within a scalable, CMOS‐compatible oxide stack. Multimodal plasticity, spike‐timing‐dependent learning, and bee‐inspired associative conditioning are achieved through trap‐mediated temporal dynamics.
Youngbin Yoon, Jaehee Lee, Jeongwook Kwon, Yongki Kim, Myunghun Shin, Jung Wook Lim   +5 more
wiley   +1 more source

Retraction: Towards robot-assisted therapy for children with autism-the ontological knowledge models and reinforcement learning-based algorithms. [PDF]

Front Robot AI
Frontiers Editorial Office.
europepmc   +1 more source

Directional Latent Hybridization: Beyond Random Noise in Physics‐Informed Generative Inverse Design of Nonlinear Metamaterials

Advanced Materials Technologies, EarlyView.
A physics‐informed generative framework introduces Directional Latent Hybridization (DLH) for the deterministic inverse design of nonlinear metamaterials. By hybridizing dominant traits from parent geometries in the latent space, DLH overcomes the instabilities of stochastic models to ensure high structural precision at high densities.
Semin Ahn, Jun Young Choi, Sung‐Hoon Ahn   +2 more
wiley   +1 more source

Efficient robot navigation inspired by honeybee learning flights. [PDF]

Nature
Ou D, Hagenaars JJ, Jankowski MR, Firlefyn MVM, De Wagter C, Muijres FT, Degen J, de Croon GCHE.   +7 more
europepmc   +1 more source

Flexible Tactile Actuator Arrays With Integrated Electroosmotic Pumps for Wearable Haptic Systems

Advanced Materials Technologies, EarlyView.
1 ×$\times$ 9 and 4 ×$\times$ 4 flexible tactile actuator arrays integrating electroosmotic pumps are developed to deliver pressure and vibration feedback on wearable platforms. Their thin, compliant structure conforms seamlessly to curved body surfaces, providing intimate contact and enhanced haptic sensations.
Heejin Yu, Joonbum Bae
wiley   +1 more source

From cheek to ureter: initial experience and learning curve of single-port robotic buccal mucosa graft ureteroplasty for complex strictures. [PDF]

J Robot Surg
Qi JC, Yang HX, Wang DB, Tang S, Wang RL, Santodirocco L, Alkassis M, Calvo RS, Xue WY, Wang YX, Crivellaro S.   +10 more
europepmc   +1 more source

Soft Robotic Excretory Care Simulator for Nursing Education: Functional and Perceptual Biomimetics Approach

Advanced Robotics Research, EarlyView.
A soft robotic simulator is developed to replicate the digital removal of feces (DRF), a sensitive yet essential nursing procedure. Integrating soft actuators, sensors, and a realistic rectal model, the simulator balances functional fidelity with perceptual realism. Engineering evaluations and nurse feedback confirm its potential to enhance training in
Shoko Miyagawa, Sota Suzuki, Shizuka Watanabe, Zebing Mao, Young Ah Seong, Toshinori Fujie, Tatsuhiro Horii, Kenjiro Tadakuma, Koichi Suzumori, Hiroyuki Nabae, Shingo Maeda   +10 more
wiley   +1 more source

Editorial: Physical AI and robotics - outputs from IS-PAIR 2025 and beyond. [PDF]

Front Robot AI
Manoonpong P, Shigaki S, Chaichaowarat R, Shamonin M.   +3 more
europepmc   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

Advanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari, Zhaoting Li, Robert Babuška, Jens Kober, Cosimo Della Santina   +4 more
wiley   +1 more source

Adaptive Control of the Redundant Axis of a Surgical Robot for Operating Room Workspace Optimization Using Reinforcement Learning. [PDF]

Sensors (Basel)
Renedo-Alonso I, Sánchez-Margallo JA, Arana-Arexolaleiba N, Elguea-Aguinaco Í.   +3 more
europepmc   +1 more source