9,192 research outputs found
Learning Feedback Terms for Reactive Planning and Control
With the advancement of robotics, machine learning, and machine perception,
increasingly more robots will enter human environments to assist with daily
tasks. However, dynamically-changing human environments requires reactive
motion plans. Reactivity can be accomplished through replanning, e.g.
model-predictive control, or through a reactive feedback policy that modifies
on-going behavior in response to sensory events. In this paper, we investigate
how to use machine learning to add reactivity to a previously learned nominal
skilled behavior. We approach this by learning a reactive modification term for
movement plans represented by nonlinear differential equations. In particular,
we use dynamic movement primitives (DMPs) to represent a skill and a neural
network to learn a reactive policy from human demonstrations. We use the well
explored domain of obstacle avoidance for robot manipulation as a test bed. Our
approach demonstrates how a neural network can be combined with physical
insights to ensure robust behavior across different obstacle settings and
movement durations. Evaluations on an anthropomorphic robotic system
demonstrate the effectiveness of our work.Comment: 8 pages, accepted to be published at ICRA 2017 conferenc
Cosmic Dawn and Epoch of Reionization Foreground Removal with the SKA
The exceptional sensitivity of the SKA will allow observations of the Cosmic
Dawn and Epoch of Reionization (CD/EoR) in unprecedented detail, both
spectrally and spatially. This wealth of information is buried under Galactic
and extragalactic foregrounds, which must be removed accurately and precisely
in order to reveal the cosmological signal. This problem has been addressed
already for the previous generation of radio telescopes, but the application to
SKA is different in many aspects.
In this chapter we summarise the contributions to the field of foreground
removal in the context of high redshift and high sensitivity 21-cm
measurements. We use a state-of-the-art simulation of the SKA Phase 1
observations complete with cosmological signal, foregrounds and
frequency-dependent instrumental effects to test both parametric and
non-parametric foreground removal methods. We compare the recovered
cosmological signal using several different statistics and explore one of the
most exciting possibilities with the SKA --- imaging of the ionized bubbles.
We find that with current methods it is possible to remove the foregrounds
with great accuracy and to get impressive power spectra and images of the
cosmological signal. The frequency-dependent PSF of the instrument complicates
this recovery, so we resort to splitting the observation bandwidth into smaller
segments, each of a common resolution.
If the foregrounds are allowed a random variation from the smooth power law
along the line of sight, methods exploiting the smoothness of foregrounds or a
parametrization of their behaviour are challenged much more than non-parametric
ones. However, we show that correction techniques can be implemented to restore
the performances of parametric approaches, as long as the first-order
approximation of a power law stands.Comment: Accepted for publication in the SKA Science Book 'Advancing
Astrophysics with the Square Kilometre Array', to appear in 201
Implementation of UAV Coordination Based on a Hierarchical Multi-UAV Simulation Platform
In this paper, a hierarchical multi-UAV simulation platform,called XTDrone,
is designed for UAV swarms, which is completely open-source 4 . There are six
layers in XTDrone: communication, simulator,low-level control, high-level
control, coordination, and human interac-tion layers. XTDrone has three
advantages. Firstly, the simulation speedcan be adjusted to match the computer
performance, based on the lock-step mode. Thus, the simulations can be
conducted on a work stationor on a personal laptop, for different purposes.
Secondly, a simplifiedsimulator is also developed which enables quick algorithm
designing sothat the approximated behavior of UAV swarms can be observed
inadvance. Thirdly, XTDrone is based on ROS, Gazebo, and PX4, andhence the
codes in simulations can be easily transplanted to embeddedsystems. Note that
XTDrone can support various types of multi-UAVmissions, and we provide two
important demos in this paper: one is aground-station-based multi-UAV
cooperative search, and the other is adistributed UAV formation flight,
including consensus-based formationcontrol, task assignment, and obstacle
avoidance.Comment: 12 pages, 10 figures. And for the, see
https://gitee.com/robin_shaun/XTDron
The FHD/ppsilon Epoch of Reionization Power Spectrum Pipeline
Epoch of Reionization data analysis requires unprecedented levels of accuracy
in radio interferometer pipelines. We have developed an imaging power spectrum
analysis to meet these requirements and generate robust 21 cm EoR measurements.
In this work, we build a signal path framework to mathematically describe each
step in the analysis, from data reduction in the FHD package to power spectrum
generation in the ppsilon package. In particular, we focus on the
distinguishing characteristics of FHD/ppsilon: highly accurate
spectral calibration, extensive data verification products, and end-to-end
error propagation. We present our key data analysis products in detail to
facilitate understanding of the prominent systematics in image-based power
spectrum analyses. As a verification to our analysis, we also highlight a
full-pipeline analysis simulation to demonstrate signal preservation and lack
of signal loss. This careful treatment ensures that the
FHD/ppsilon power spectrum pipeline can reduce radio
interferometric data to produce credible 21 cm EoR measurements.Comment: 21 pages, 10 figures, accepted by PAS
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