Results 151 to 160 of about 863,292 (347)

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

Nonlocomotory Robotic Strategies for Dynamic Rotation Control in Terrestrial Robots: A Review

open access: yesAdvanced Robotics Research, EarlyView.
Terrestrial robots increasingly require rapid body rotation to maintain stability and agility in complex environments. This review shows nonlocomotory rotational control strategies that operate without ground contact, including reaction wheels, tails, bars, limbs, and thrusters.
Y. Liang   +14 more
wiley   +1 more source

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

open access: yesAdvanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Soft Actuators Integrated with Control and Power Units: Approaching Wireless Autonomous Soft Robots

open access: yesAdvanced Robotics Research, EarlyView.
Soft robots exhibit significant development potential in various applications. However, there are still key technical challenges regarding material improvement, structure design and components integration. This review focuses on the development and challenge of soft actuators, power components, and control components in untethered intelligent soft ...
Renwu Shi, Feifei Pan, Xiaobin Ji
wiley   +1 more source

Backpropagation Through Soft Body: Investigating Information Processing in Brain–Body Coupling Systems

open access: yesAdvanced Robotics Research, EarlyView.
This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka   +3 more
wiley   +1 more source

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

open access: yesAdvanced 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   +7 more
wiley   +1 more source

3D‐Printing Aided Rapid Prototyping of Pretensioned Tensegrity Structures for Robotic Applications

open access: yesAdvanced Robotics Research, EarlyView.
Printing, injection molding, and assembly (PMA) is a method for rapid prototyping mesoscale, topologically complex, and tensioned tensegrity structures. In combination with PMA method, two mold design strategies: modular mold and compact channel layout, enable efficiency and scalability for tensegrity fabrication.
Yi Sun   +3 more
wiley   +1 more source

Validity of Word Lists for Assessing Attentional Biases Involving Appearance: A Semantic Differential Approach

open access: yesJournal of Experimental Psychopathology
We aimed to validate word lists developed by Tabri and Palmer (2020) for use in attentional bias research on appearance-related concerns. Three lists contained appearance words (attractiveness, stigmatized appearance, general appearance), and three ...
Thalia Charlebois   +6 more
doaj   +1 more source

AutomataGPT: Transformer‐Based Forecasting and Ruleset Inference for Two‐Dimensional Cellular Automata

open access: yesAdvanced Science, EarlyView.
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich   +2 more
wiley   +1 more source

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