Results 101 to 110 of about 24,273 (264)
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
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
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
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
A Survey of Robot Intelligence with Large Language Models
Since the emergence of ChatGPT, research on large language models (LLMs) has actively progressed across various fields. LLMs, pre-trained on vast text datasets, have exhibited exceptional abilities in understanding natural language and planning tasks ...
Hyeongyo Jeong +3 more
doaj +1 more source
The purpose of robot vision is to enable robots to perceive the external world in order to perform a large range of tasks such as navigation, visual servoing for object tracking and manipulation, object recognition and categorization, surveillance, and higher-level decision-making.
openaire +2 more sources
Soft Actuators Integrated with Control and Power Units: Approaching Wireless Autonomous Soft Robots
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
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source
This review identifies key design considerations for insect‐inspired microrobots capable of multimodal locomotion. To draw inspiration, biological and robotic strategies for moving in air, on water surfaces, and underwater are examined, along with approaches for crossing the air–water interface.
Mija Jovchevska +2 more
wiley +1 more source
Degradable Magnetic Composites from Recycled NdFeB Magnets for Soft Actuation and Sensing
This work presents a degradable soft magnetic composite made from recycled NdFeB particles embedded in a gelatin‐based organogel. The material is processed into magnetic sensors and soft robotic components, which can later be dissolved in a green solvent to recover NdFeB magnetic particles.
Muhammad Bilal Khan +14 more
wiley +1 more source
Vision based robot-to-robot object handover [PDF]
Monica Sileo +3 more
openaire +1 more source

