Results 181 to 190 of about 149,166 (264)

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

Advanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi, Amirreza Davar, Dongyi Wang   +2 more
wiley   +1 more source

Deep learning in ventral hernia imaging: automated multi-structure CT segmentation for surgical planning. [PDF]

J Abdom Wall Surg
Rengan V, Meenashi Sundaram P, Arora E, Girieasen S, Bawa A, Alexander N, Ravanasamudram Sitaraman R, Reddy V, Kalikar V, Arora A, Kona L, Venkataramanan R, Lalwani D, Meenashi Sundaram D, Kalla R.   +14 more
europepmc   +1 more source

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

Clinical-guided deep learning framework for diabetic retinopathy: integrating lesion-aware attention, adversarial augmentation, and uncertainty quantification. [PDF]

Sci Rep
Saleem S, Talib R, Hanif MK, Sarwar MU.
europepmc   +1 more source

Lightweight Automated Reasoning for Network Architectures

Proceedings of the 23rd ACM Workshop on Hot Topics in Networks
Rahul Bothra, Venkat Arun, Brighten Godfrey, Akshay Narayan 0001, Ahmed Saeed 0001   +4 more
openaire   +2 more sources

Universal Gripper for Industrial Manipulation With Enhanced Rigid Mechanics and Self‐Adaptable Fingers

Advanced Robotics Research, EarlyView.
An enhanced universal gripper combining rigid mechanics with self‐adaptable fingers is presented for industrial automation. The novel six‐bar linkage with integrated compliant pad eliminates mechanical interference while enabling passive shape adaptation.
Muhammad Usman Khalid, Nirmal Kumar Ravikumar, Mattia Frascio, Sumanth Nagalakunta, Alessandro Seitone, Benoît Lévesque, Alessandro Zanella, Matteo Zoppi   +7 more
wiley   +1 more source

A Secure, Scalable Large Language Model-Based System (CIDER) for High-Throughput Clinical Data Extraction From Medical Reports: Retrospective Validation Study. [PDF]

J Med Internet Res
Posta M, Figler A, Dobolyi Z, Győrffy B.   +3 more
europepmc   +1 more source

A Multidirectional Textile Interface for Remote Control Using Dynamic Area‐Based Capacitance Modulation

Advanced Robotics Research, EarlyView.
Here, we present a textile, wearable capacitive interface enabling multidirectional remote control by dynamically modulating electrode overlap and spacing via a freely gliding upper electrode. A forearm‐mounted prototype drives robotic and media tasks with 12–15 ms latency, maintains < 0.8% drift after 500 cycles, and remains stably functional at 90 ...
Cagatay Gumus, Fulya Yenilmez, Kadir Ozlem, Hakan Kestir, Eren Tasdemir, Berkant Bakisli, Gökhan Ince, Ozgur Atalay, Asli Tuncay Atalay   +8 more
wiley   +1 more source

Cyber resilience across domains: an in-depth exploration of cybersecurity practices and paradigms from the home environment to Operational Technology (OT). [PDF]

Sci Rep
Sakthivel T, Balasubramanian K.
europepmc   +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

Advanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao, Hongzhou Ai, Wenjun Xu, Zude Zhou, Lihui Wang   +4 more
wiley   +1 more source