Research on active collision avoidance control technology for intelligent connected monorail transit trains in the virtual coupling environment. [PDF]
Hou Z, Liang H, Yang G, Han J.
europepmc +1 more source
Evolution of Physical Intelligence Across Scales
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu +7 more
wiley +1 more source
Autonomous robots with socially-aware navigation using memory-assisted deep reinforcement learning. [PDF]
Montero E +4 more
europepmc +1 more source
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
Gradient-Based Time-Sequential Potential Field Method for Path Planning in Infrastructure-Based Cooperative Driving Automation. [PDF]
Ko J, Yang I.
europepmc +1 more source
Self‐Sensing Artificial‐Muscle‐Empowered Humanlike Perception, Interaction, and Positioning
The proposed self‐sensorized artificial muscle (SSAM) can sense its length change as small as 0.01 mm via a seamlessly integrated multi‐segment induction coil. The SSAM provides accurate length information regardless of its loadings, driving pressure, or muscle design, adequate for robust data‐driven feedback control.
Houping Wu +6 more
wiley +1 more source
An Enhanced A*-DWA Fusion Algorithm for Robot Navigation in Complex Environments. [PDF]
Bao H +5 more
europepmc +1 more source
It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar +2 more
wiley +1 more source
Coulomb force-guided deep reinforcement learning for effective and explainable robotic motion planning. [PDF]
Song S, Bihl T, Liu J.
europepmc +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source

