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
Continuum Mechanics Modeling of Flexible Spring Joints in Surgical Robots
A new mechanical model of a tendon‐actuated helical extension spring joint in surgical robots is built using Cosserat rod theory. The model can implicitly handle the unknown contacts between adjacent coils and numerically predict spring shapes from straight to significantly bent under actuation forces.
Botian Sun +3 more
wiley +1 more source
Type-II neural symmetry detection with Lie theory. [PDF]
Gabel A, Quax R, Gavves E.
europepmc +1 more source
Numerical Modeling of Photothermal Self‐Excited Composite Oscillators
We present a numerical framework for simulating photothermal self‐excited oscillations. The driving mechanism is elucidated by highlighting the roles of inertia and overshoot, as well as the phase lag between the thermal moment and the oscillation angle, which together construct the feedback loop between the system state and the environmental stimulus.
Zixiao Liu +6 more
wiley +1 more source
Particle swarm optimization based analysis to unlocking the neutrino mass puzzle using [Formula: see text] flavor symmetry. [PDF]
Aslam MW +6 more
europepmc +1 more source
High‐Performance Graphene‐Based Gas Sensors with Pulsed Heating and AI Processing
Ultra‐low power graphene‐based MEMS gas sensors functionalized with vanadium pentoxide or copper‐manganese oxide are reported. Operated in pulsed heating mode, the sensors produce transient conductance profiles analyzed via discrete Fourier transform and compact neural networks.
Paniz Vafaei +10 more
wiley +1 more source
Atomic pair distribution functions from textured polycrystalline samples: fundamentals. [PDF]
Gong Z, Tao S, Billinge SJL.
europepmc +1 more source
Leveraging Transfer Learning to Overcome Data Limitations in Czochralski Crystal Growth
A data‐driven framework combining Computational Fluid Dynamics (CFD) simulations and machine learning is proposed to model and optimize Czochralski crystal growth. Using different transfer learning strategies (Warm Start, Merged Training, and Hyperparameter Transfer) the study demonstrates improved predictions for Ge and GaAs growth from Si‐trained ...
Milena Petkovic +3 more
wiley +1 more source
New approaches for capturing and estimating variation in complex animal color patterns from digital photographs: application to the Eastern Box Turtle (<i>Terrapene carolina</i>). [PDF]
Maki E +4 more
europepmc +1 more source

