Results 171 to 180 of about 87,603 (273)

Interactive Prompt‐Guided Robotic Grasping for Arbitrary Objects Based on Promptable Segment Anything Model and Force‐Closure Analysis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu, Yaxin Liu, Ruiqing Han, Kai Zheng, Yufeng Yao, Ming Zhong   +5 more
wiley   +1 more source

Learning Continuous Decomposable Models Using Mutual Information and Statistical Copulas. [PDF]

Entropy (Basel)
Desuó Neto L, de Oliveira Caetano H, de Souza Sant'Anna Fogliatto M, Dias Maciel C.   +3 more
europepmc   +1 more source

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

A Novel Parameter Estimation Method for Pneumatic Soft Hand Control Applying Logarithmic Decrement for Pseudo‐Rigid Body Modeling

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
In this research, a paradigm of parameter estimation method for pneumatic soft hand control is proposed. The method includes the following: 1) sampling harmonic damping waves, 2) applying pseudo‐rigid body modeling and the logarithmic decrement method, and 3) deriving position and force control.
Haiyun Zhang, Kelvin HoLam Heung, Gabrielle J. Naquila, Ashwin Hingwe, Ashish D. Deshpande   +4 more
wiley   +1 more source

A maximal-coverage approach to prioritizing newborn sickle cell screening sites in Uganda using a sickle cell-malaria co-risk surface. [PDF]

Malar J
Paasi G, Ndeezi G, Kiyaga C, Namazzi R, Mupere E, Munabi IG, Kiguli S, Idro R, Olupot-Olupot P.   +8 more
europepmc   +1 more source

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Towards Dynamic V2X Infrastructure: Joint Deployment and Optimization of 6DMA-Enabled RSUs. [PDF]

Sensors (Basel)
Wu X, Huang R, Wei C, Chu X, Chen J, Zhao S.   +5 more
europepmc   +1 more source

Characteristics, Management, and Utilization of Muscles in Musculoskeletal Humanoids: Empirical Study on Kengoro and Musashi

Advanced Intelligent Systems, EarlyView.
Musculoskeletal humanoids exhibit rich biomechanical properties that remain insufficiently unified in prior discussions. This article systematically categorizes muscle characteristics into five properties: redundancy, independency, anisotropy, variable moment arm, and nonlinear elasticity, and analyzes their combined effects on control.
Kento Kawaharazuka, Kei Okada, Masayuki Inaba   +2 more
wiley   +1 more source

DRLO-VANET: a deep reinforcement learning-based offloading framework for low-latency and energy-efficient task execution in VANETs. [PDF]

Sci Rep
Neelima S, Sree SR, Ramakrishnaiah N.
europepmc   +1 more source

Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining

Advanced Intelligent Systems, EarlyView.
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson, Nebojša Maleševic, Anders Björkman, Christian Antfolk   +3 more
wiley   +1 more source