100,148 research outputs found
Vast planes of satellites in a high resolution simulation of the Local Group: comparison to Andromeda
We search for vast planes of satellites (VPoS) in a high resolution
simulation of the Local Group performed by the CLUES project, which improves
significantly the resolution of former similar studies. We use a simple method
for detecting planar configurations of satellites, and validate it on the known
plane of M31. We implement a range of prescriptions for modelling the satellite
populations, roughly reproducing the variety of recipes used in the literature,
and investigate the occurence and properties of planar structures in these
populations. The structure of the simulated satellite systems is strongly
non-random and contains planes of satellites, predominantly co-rotating, with,
in some cases, sizes comparable to the plane observed in M31 by Ibata et al..
However the latter is slightly richer in satellites, slightly thinner and has
stronger co-rotation, which makes it stand out as overall more exceptional than
the simulated planes, when compared to a random population. Although the
simulated planes we find are generally dominated by one real structure, forming
its backbone, they are also partly fortuitous and are thus not kinematically
coherent structures as a whole. Provided that the simulated and observed planes
of satellites are indeed of the same nature, our results suggest that the VPoS
of M31 is not a coherent disc and that one third to one half of its satellites
must have large proper motions perpendicular to the plane
Aggressive Quadrotor Flight through Narrow Gaps with Onboard Sensing and Computing using Active Vision
We address one of the main challenges towards autonomous quadrotor flight in
complex environments, which is flight through narrow gaps. While previous works
relied on off-board localization systems or on accurate prior knowledge of the
gap position and orientation, we rely solely on onboard sensing and computing
and estimate the full state by fusing gap detection from a single onboard
camera with an IMU. This problem is challenging for two reasons: (i) the
quadrotor pose uncertainty with respect to the gap increases quadratically with
the distance from the gap; (ii) the quadrotor has to actively control its
orientation towards the gap to enable state estimation (i.e., active vision).
We solve this problem by generating a trajectory that considers geometric,
dynamic, and perception constraints: during the approach maneuver, the
quadrotor always faces the gap to allow state estimation, while respecting the
vehicle dynamics; during the traverse through the gap, the distance of the
quadrotor to the edges of the gap is maximized. Furthermore, we replan the
trajectory during its execution to cope with the varying uncertainty of the
state estimate. We successfully evaluate and demonstrate the proposed approach
in many real experiments. To the best of our knowledge, this is the first work
that addresses and achieves autonomous, aggressive flight through narrow gaps
using only onboard sensing and computing and without prior knowledge of the
pose of the gap
Slow Adaptive OFDMA Systems Through Chance Constrained Programming
Adaptive OFDMA has recently been recognized as a promising technique for
providing high spectral efficiency in future broadband wireless systems. The
research over the last decade on adaptive OFDMA systems has focused on adapting
the allocation of radio resources, such as subcarriers and power, to the
instantaneous channel conditions of all users. However, such "fast" adaptation
requires high computational complexity and excessive signaling overhead. This
hinders the deployment of adaptive OFDMA systems worldwide. This paper proposes
a slow adaptive OFDMA scheme, in which the subcarrier allocation is updated on
a much slower timescale than that of the fluctuation of instantaneous channel
conditions. Meanwhile, the data rate requirements of individual users are
accommodated on the fast timescale with high probability, thereby meeting the
requirements except occasional outage. Such an objective has a natural chance
constrained programming formulation, which is known to be intractable. To
circumvent this difficulty, we formulate safe tractable constraints for the
problem based on recent advances in chance constrained programming. We then
develop a polynomial-time algorithm for computing an optimal solution to the
reformulated problem. Our results show that the proposed slow adaptation scheme
drastically reduces both computational cost and control signaling overhead when
compared with the conventional fast adaptive OFDMA. Our work can be viewed as
an initial attempt to apply the chance constrained programming methodology to
wireless system designs. Given that most wireless systems can tolerate an
occasional dip in the quality of service, we hope that the proposed methodology
will find further applications in wireless communications
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