Results 101 to 110 of about 166,958 (306)
Advanced Materials, EarlyView.We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano +5 more
wiley +1 more source
LIMIT THEOREMS FOR SEQUENCES OF RANDOM TREES
, 2014 . We consider a random tree and introduce a metric in the space of trees to define the “mean tree ” as the tree minimizing the average distance to the random tree. When the resulting metric space is compact we show laws of large numbers and central limit
David Balding +3 more
core
A survey of path planning of industrial robots based on rapidly exploring random trees. [PDF]
Front Neurorobot, 2023 Luo S, Zhang M, Zhuang Y, Ma C, Li Q.
europepmc +1 more source
A Hybrid Computational Framework for PCF‐based SPR Sensor With Machine Learning and xAI
Advanced Materials Interfaces, EarlyView.A photonic crystal fiber‐based surface plasmon resonance (SPR) sensor integrating rectangular air holes along with conventional circular air holes achieves exceptional wavelength sensitivity of 15,000 nm/RIU across a broad refractive index range of 1.31–1.39. Integrated machine learning with explainable AI (xAI) models achieves high prediction accuracy
Mahabur Rahman Fahim +3 more
wiley +1 more source
Development of an Improved Rapidly Exploring Random Trees Algorithm for Static Obstacle Avoidance in Autonomous Vehicles. [PDF]
Sensors (Basel), 2021 Yang SM, Lin YA.
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
European Journal of Combinatorics, 1986 Let T be a locally finite, infinite tree. The simple random walk on T is the Markov chain on T with transition probabilities \(p(v,w)=1/d(v)\) if v, w are adjacent vertices, and \(p(v,w)=0\) otherwise, where d(v) is the degree of the vertex v. In this paper the authors investigate recurrence properties of tree and relations between the radius of ...
Peter Gerl, Wolfgang Woess
openaire +1 more source
Muscle Control of an Extra Robotic Digit
Advanced Robotics Research, EarlyView.This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ +7 more
wiley +1 more source
Mean Path Lengths in a Class of Recursive Random Trees [PDF]
, 1976 An operation of addition is defined on the set of random trees and a class of random trees which may be constructed by repeated application of this process is studied. These trees are, rather distantly, related to those which occur in some algorithms for
Clowes JS
core
LLM‐Integrated Human–Robot Interaction System for Microrobots
Advanced Robotics Research, EarlyView.This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley +1 more source