5,761 research outputs found
LO-Net: Deep Real-time Lidar Odometry
We present a novel deep convolutional network pipeline, LO-Net, for real-time
lidar odometry estimation. Unlike most existing lidar odometry (LO) estimations
that go through individually designed feature selection, feature matching, and
pose estimation pipeline, LO-Net can be trained in an end-to-end manner. With a
new mask-weighted geometric constraint loss, LO-Net can effectively learn
feature representation for LO estimation, and can implicitly exploit the
sequential dependencies and dynamics in the data. We also design a scan-to-map
module, which uses the geometric and semantic information learned in LO-Net, to
improve the estimation accuracy. Experiments on benchmark datasets demonstrate
that LO-Net outperforms existing learning based approaches and has similar
accuracy with the state-of-the-art geometry-based approach, LOAM
Equations of motion of test particles for solving the spin-dependent Boltzmann-Vlasov equation
A consistent derivation of the equations of motion (EOMs) of test particles
for solving the spin-dependent Boltzmann-Vlasov equation is presented. The
resulting EOMs in phase space are similar to the canonical equations in
Hamiltonian dynamics, and the EOM of spin is the same as that in the Heisenburg
picture of quantum mechanics. Considering further the quantum nature of spin
and choosing the direction of total angular momentum in heavy-ion reactions as
a reference of measuring nucleon spin, the EOMs of spin-up and spin-down
nucleons are given separately. The key elements affecting the spin dynamics in
heavy-ion collisions are identified. The resulting EOMs provide a solid
foundation for using the test-particle approach in studying spin dynamics in
heavy-ion collisions at intermediate energies. Future comparisons of model
simulations with experimental data will help constrain the poorly known
in-medium nucleon spin-orbit coupling relevant for understanding properties of
rare isotopes and their astrophysical impacts.Comment: 5 page
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