Results 61 to 70 of about 12,871 (286)
Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics
This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang +5 more
wiley +1 more source
Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space
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
On syntactic and semantic action refinement [PDF]
The semantic definition of action refinement on labelled event structures is compared with the notion of syntactic substitution,which can be used as another notion of action refiment in a process algebraic setting. This is done by studying a process algebra equipped with the ACP sequential composition, parallel composition with an explicit ...
Goltz, U., Gorrieri, R., Rensink, Arend
openaire +2 more sources
The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?
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
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
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
Segmenting Action-Value Functions over Time Scales in SARSA via TD(Δ)
In numerous episodic reinforcement learning (RL) environments, SARSA-based methodologies are employed to enhance policies aimed at maximizing returns over long horizons. Traditional SARSA algorithms face challenges in achieving an optimal balance between
Mahammad Humayoo +10 more
doaj +1 more source
Differential Invariants of Measurements, and Their Relation to Central Moments
Due to the principle of minimal information gain, the measurement of points in an affine space V determines a Legendrian submanifold of V×V*×R. Such Legendrian submanifolds are equipped with additional geometric structures that come from the central ...
Eivind Schneider
doaj +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
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
UNCONTROLLABILITY AND TEMPORALITY
The paper considers the influence of the semantics of uncontrollability on the use of verbs in different tense forms.
T. G. Pismak
doaj

