Results 171 to 180 of about 3,198,815 (270)

Liquid Metal Sensors for Soft Robots

Advanced Robotics Research, EarlyView.
This review thoroughly reviews liquid metal sensors in soft robots. Their unique material properties like high conductivity and good biocompatibility are analyzed. Working principles are classified, and applications in environmental perception, motion detection, and human—robot interaction are introduced.
Qi Zhang, Nan Li, Yujia Song, Chen Hua, Tangzhen Guan, Yibing Ma, Cai Cheng, Jing Liu   +7 more
wiley   +1 more source

Identification and validation of respiratory virus immunization using natural language processing. [PDF]

Front Digit Health
Wilson KA, Riddles JJ, Hill AC, Bassett EA, Zhou M, Barron M, Chavez C, Shrivastava R, Battalahalli A, Chacreton D, Moran E, Rowley E, Weber ZA, Reichle L, Ball SW, Payne AB, DeCuir J, Link-Gelles R, Ong TC.   +18 more
europepmc   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

A robust natural language text-to-SQL generation framework with dynamic strategies based on LLMs. [PDF]

Sci Rep
Su X, Gu Y, Wang P, Gu W, Qi L, He J.
europepmc   +1 more source

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

Advanced Robotics Research, EarlyView.
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat, Ali Umut Kaypak, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami   +4 more
wiley   +1 more source

Accurate and Scalable Classification of Colonoscopy Neoplasia Using Machine Learning and Natural Language Processing. [PDF]

Clin Transl Gastroenterol
Broderick B, Greenwood J, Mahoney D, Burger K, Garg SK, Wallace MB, Gurudu SR, Ebner D, Kisiel J.   +8 more
europepmc   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Natural language processing algorithm accurately classifies diverticulitis-related complications and predicts long-term outcomes. [PDF]

Clin Gastroenterol Hepatol
Ma W, Wu Y, Challa PK, Sikavi D, Downie JM, Nguyen LH, Raghu VK, Simon TG, Khalili H, Kambadakone AR, Ananthakrishnan AN, Strate LL, Chan AT.   +12 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

Linking subjective experience of anxiety to brain function using natural language processing. [PDF]

Soc Cogn Affect Neurosci
Kirk PA, Qamar P, Lentz J, Zugman A, Abend R, Kircanski K, Pine DS.   +6 more
europepmc   +1 more source