Results 101 to 110 of about 23,336 (274)
Between-subject variability of muscle synergies during a complex motor skill
Frontiers in Computational Neuroscience, 2012 The purpose of the present study was to determine whether subjects who have learned a complex motor skill exhibit similar neuromuscular control strategies. We studied a population of experienced gymnasts during backward giant swings on the high bar. This
Julien eFrère, François eHug
doaj +1 more source
Scalable Task Planning via Large Language Models and Structured World Representations
Advanced Robotics Research, EarlyView.This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari +4 more
wiley +1 more source
Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space
Advanced Robotics Research, EarlyView.A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo +6 more
wiley +1 more source
A Taxonomy of Functional Upper Extremity Motion
Frontiers in Neurology, 2019 Background: Functional upper extremity (UE) motion enables humans to execute activities of daily living (ADLs). There currently exists no universal language to systematically characterize this type of motion or its fundamental building blocks, called ...
Heidi M. Schambra +6 more
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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 +4 more
wiley +1 more source
Advanced Robotics Research, EarlyView.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
On the Kinematic Motion Primitives (kMPs) - Theory and Application
Frontiers in Neurorobotics, 2012 Human neuromotor capabilities guarantee a wide variety of motions. A full understanding of human motion can be beneficial for rehabilitation or performance enhancement purposes, or for its reproduction on artificial systems like robots. This work aims at
Federico Lorenzo Moro +2 more
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Advanced Robotics Research, EarlyView.This work presents the MicroRoboScope, a highly integrated, compact, and portable microrobotic experimentation platform combining electromagnetic and acoustic actuation with real‐time visual feedback into a single, end‐to‐end device. The system enables closed‐loop control and tracking algorithm experimentation within an accessible and unified hardware ...
Max Sokolich +4 more
wiley +1 more source
Frontiers in Computational Neuroscience, 2018 One of the current challenges in human motor rehabilitation is the robust application of Brain-Machine Interfaces to assistive technologies such as powered lower limb exoskeletons.
Andrés Úbeda +4 more
doaj +1 more source
Neural probabilistic motor primitives for humanoid control
, 2018 Accepted as a conference paper at ICLR ...
Merel, J +7 more
openaire +3 more sources