14,328 research outputs found
Flexible Stereo: Constrained, Non-rigid, Wide-baseline Stereo Vision for Fixed-wing Aerial Platforms
This paper proposes a computationally efficient method to estimate the
time-varying relative pose between two visual-inertial sensor rigs mounted on
the flexible wings of a fixed-wing unmanned aerial vehicle (UAV). The estimated
relative poses are used to generate highly accurate depth maps in real-time and
can be employed for obstacle avoidance in low-altitude flights or landing
maneuvers. The approach is structured as follows: Initially, a wing model is
identified by fitting a probability density function to measured deviations
from the nominal relative baseline transformation. At run-time, the prior
knowledge about the wing model is fused in an Extended Kalman filter~(EKF)
together with relative pose measurements obtained from solving a relative
perspective N-point problem (PNP), and the linear accelerations and angular
velocities measured by the two inertial measurement units (IMU) which are
rigidly attached to the cameras. Results obtained from extensive synthetic
experiments demonstrate that our proposed framework is able to estimate highly
accurate baseline transformations and depth maps.Comment: Accepted for publication in IEEE International Conference on Robotics
and Automation (ICRA), 2018, Brisban
Depth Fields: Extending Light Field Techniques to Time-of-Flight Imaging
A variety of techniques such as light field, structured illumination, and
time-of-flight (TOF) are commonly used for depth acquisition in consumer
imaging, robotics and many other applications. Unfortunately, each technique
suffers from its individual limitations preventing robust depth sensing. In
this paper, we explore the strengths and weaknesses of combining light field
and time-of-flight imaging, particularly the feasibility of an on-chip
implementation as a single hybrid depth sensor. We refer to this combination as
depth field imaging. Depth fields combine light field advantages such as
synthetic aperture refocusing with TOF imaging advantages such as high depth
resolution and coded signal processing to resolve multipath interference. We
show applications including synthesizing virtual apertures for TOF imaging,
improved depth mapping through partial and scattering occluders, and single
frequency TOF phase unwrapping. Utilizing space, angle, and temporal coding,
depth fields can improve depth sensing in the wild and generate new insights
into the dimensions of light's plenoptic function.Comment: 9 pages, 8 figures, Accepted to 3DV 201
Measurements of a rotor flow in ground effect and visualization of the brown-out phenomenon
Quantitative and qualitative results of a series of experiments conducted on a rotor in ground effect at low
forward speeds are presented. The velocity over a wide area of the ground effect wake was measured using Particle Image Velocimetry (PIV), and the evolution of the flow is described as the forward speed increases. Helicopter brown-out was simulated through a series of flow visualisation experiments. The technique involved sprinkling a fine powder on the ground below and ahead of the rotor. This helps to validate the experimental simulation of the brown-out phenomenon. Larger dust clouds were observed at lower advance ratio, and the dust cloud penetrated into the areas of the flow including those where vorticity levels were of low or negligible magnitude
Bioinspired engineering of exploration systems for NASA and DoD
A new approach called bioinspired engineering of exploration systems (BEES) and its value for solving pressing NASA and DoD needs are described. Insects (for example honeybees and dragonflies) cope remarkably well with their world, despite possessing a brain containing less than 0.01% as many neurons as the human brain. Although most insects have immobile eyes with fixed focus optics and lack stereo vision, they use a number of ingenious, computationally simple strategies for perceiving their world in three dimensions and navigating successfully within it. We are distilling selected insect-inspired strategies to obtain novel solutions for navigation, hazard avoidance, altitude hold, stable flight, terrain following, and gentle deployment of payload. Such functionality provides potential solutions for future autonomous robotic space and planetary explorers. A BEES approach to developing lightweight low-power autonomous flight systems should be useful for flight control of such biomorphic flyers for both NASA and DoD needs. Recent biological studies of mammalian retinas confirm that representations of multiple features of the visual world are systematically parsed and processed in parallel. Features are mapped to a stack of cellular strata within the retina. Each of these representations can be efficiently modeled in semiconductor cellular nonlinear network (CNN) chips. We describe recent breakthroughs in exploring the feasibility of the unique blending of insect strategies of navigation with mammalian visual search, pattern recognition, and image understanding into hybrid biomorphic flyers for future planetary and terrestrial applications. We describe a few future mission scenarios for Mars exploration, uniquely enabled by these newly developed biomorphic flyers
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