Results 161 to 170 of about 816,103 (361)

Shaping Carbon Nitrides for Advanced Macrostructures

Advanced Materials Technologies, EarlyView.
This review examines how carbon nitride can be shaped through a range of printing and interfacial assembly methods. By bringing together additive manufacturing and liquid–liquid structuring concepts, carbon nitride is moving beyond its traditional powder‐based photocatalyst form toward digitally designed robust macroscale architectures with high design
Simona Baluchová, Baris Kumru
wiley   +1 more source

Combining electrical stimulation mediated by iterative learning control with movement practice using real objects and simulated tasks for post-stroke upper extremity rehabilitation

, 2014
Objective: task specific training and Electrical stimulation (ES) are techniques used in rehabilitation of the upper extremity post stroke. This study describes the feasibility of using a rehabilitation system that combines personalised, precisely ...
Kutlu, M., Hallewell, Emma, Hughes,, A. M., Freeman, Christopher, Meadmore, Katie, Hughes, Ann-Marie, Kutlu, Mustafa, Freeman, C., Meadmore, K.   +8 more
core  

Multimodal Haptic Perception Through Synergistic Nanocomposite Sensor Arrays

Advanced Materials Technologies, EarlyView.
Multi‐modal fingertip haptics are advanced through a bioinspired &vertical‐via' electronic skin architecture. A confined PDMS/MWCNT/NiNP nanocomposite, sitting at the percolation threshold, enables tactile, thermal, and magnetic sensing. A unique via‐density gradient and dedicated &Un‐Touch' reference nodes provide robust spatial resolution and signal ...
Amos Bardea, Fernando Patolsky
wiley   +1 more source

Data‐Efficient Electromagnetic Surrogate Solver Through Dissipative Relaxation Transfer Learning

Advanced Optical Materials, EarlyView.
Dissipative relaxation transfer learning (DIRTL) enables data‐efficient training of electromagnetic surrogate solvers by pretraining data generated with artificial material loss before fine‐tuning on target lossless data. The framework suppresses resonant outlier effects during early training, allowing effective adaptation to high‐amplitude resonances ...
Sunghyun Nam, Chan Y. Park, Min Seok Jang   +2 more
wiley   +1 more source

The analysis of the convergence speed for an iterative learning scheme

, 2004
This paper presents an iterative learning scheme for a linear time-invariance (LTI) system. Based on the scheme, the influence of learning structure, learning laws and learning parameters on the convergence speed of iterative learning control (ILC) is ...
Xu, JX, Tan DL(谈大龙), Wang, XD, Chai, TY   +3 more
core  

Motion Planning and Iterative Learning Control of a Modular Soft Robotic Snake. [PDF]

Front Robot AI, 2020
Luo M, Wan Z, Sun Y, Skorina EH, Tao W, Chen F, Gopalka L, Yang H, Onal CD.   +8 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

PD iterative self-learning control for 3R plane robot trajectory tracking

, 2013
In order to improve the speed and accuracy of the trajectory tracking control for 3R plane robot, a PD iterative self-learning control algorithm is proposed based on the PD iterative control algorithm.
Liu JG(刘金国), Liu CY(刘传银), Leng YQ(冷雨泉), Gao HW(高宏伟), Hong, Kun   +4 more
core  

Iterative Learning Control for a Soft Exoskeleton with Hip and Knee Joint Assistance. [PDF]

Sensors (Basel), 2020
Chen C, Zhang Y, Li Y, Wang Z, Liu Y, Cao W, Wu X.   +6 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