1,136 research outputs found
Analysis and Experiment of an Ultra-light Flapping Wing Aircraft
II
Inspired by flying animals in nature especially birds, human has designed and attempted
to achieve man-powered flapping wing aircraft in very early aviation history. Limited by
the understanding of the aerodynamic theory and materials in practise, the bird-like
aircraft remains as a dream and ambition for over a contrary. As the relevant knowledge
and technology are fast developing in the last decade, the research topic becomes
attractive again with encouraging results from a few full scale aircraft flight tests.
Although it is suspected that a manned scale flapping wing may not be as efficient as
fixed wing, the unique advantages of high manoeuvrability and short take-off and
landing capability will keep flapping wing as one of the most potential type of personal
and aerobatic aircraft in the future market.
The aim of this project is to investigate into the feasibility and development of a
bio-inspired bird-like man-powered ultra-light flapping wing aircraft (ULFWA). The
project is based on analytical and experimental study of a scaled model taking an
existing hang glider as the baseline airframe. Based on the characteristics of flying
animals in nature and manmade hang glider properties, this thesis focuses its study on
evaluating the feasibility and analysis of primarily a human powered aircraft. For this
purpose, there are four main features as guidance in the ULFWA design. Firstly the
flapping frequency was limited to below 2Hz. Secondly the hang glider airframe was
adapted with a simple flapping mechanism design. Thirdly the flapping wing stroke and
kinematics has been kept with the simplest and resonant movement to achieve high
mechanical efficiency. Finally the wing structure has flexible rib of chord wise
unsymmetrical bending stiffness to offset the aerodynamic lift loss in upstroke. An
engine powered mechanism design was also studied as additional option of the ULFWA.
The initial design and aerodynamic calculation of the ULFWA was based on the hang
glider data including dimensions, MTOW (226 kg) and cruising speed. The unsteady
aerodynamic lift and thrust forces were calculated based on Theodorsen’s theory and
unsteady panel method in 2D and extended to 3D using strip theory. A set of optimal
flapping kinematic parameters such as amplitude and combination of the heaving and
pitching motion of the 2D wing section were determined by calculation and comparison
in the limited range. Considering the maximum power and lag motion that human could
achieve, the flapping frequency in the ULFWA design is limited to 1Hz. This slow motion
leads to a much lower propulsive efficiency in terms of the optimum Strouhal Number
(St=0.2-0.4), which was used as the design reference. Mechanism and structure design
with inertia force calculation was then completed based on the kinematics. This led to
the evaluation of power requirement, which was divided into two components, drag and
inertia forces. The results show that the ULFWA needs minimum 2452.25W (equals to
3.29Bhp) to maintain sustainable cruise flight.
In order to demonstrate the ULFWA flapping mechanism and structure design, a 1:10
scaled model with two pairs of wings of different stiffness were built for testing and
measurement. Two servomotors were used as to simulate human power actuation. With
this model, simplified structure and one of mechanism designs was shown. Four
experiments were carried out to measure the model’s lift and thrust force. Because of
the limited response of the servo motors, the maximum flapping frequency achieved is
only 0.75 Hz in the specified flapping amplitude which is close to reality and has
improvement margin. By reducing the flapping amplitude, the frequency can be
increased to gain higher thrust. Although it is fund that the result from scaled model test
is a little lower than theoretical result, it has demonstrated the feasibility and potential
of human powered flapping wings aircraft
3D Shape Estimation from 2D Landmarks: A Convex Relaxation Approach
We investigate the problem of estimating the 3D shape of an object, given a
set of 2D landmarks in a single image. To alleviate the reconstruction
ambiguity, a widely-used approach is to confine the unknown 3D shape within a
shape space built upon existing shapes. While this approach has proven to be
successful in various applications, a challenging issue remains, i.e., the
joint estimation of shape parameters and camera-pose parameters requires to
solve a nonconvex optimization problem. The existing methods often adopt an
alternating minimization scheme to locally update the parameters, and
consequently the solution is sensitive to initialization. In this paper, we
propose a convex formulation to address this problem and develop an efficient
algorithm to solve the proposed convex program. We demonstrate the exact
recovery property of the proposed method, its merits compared to alternative
methods, and the applicability in human pose and car shape estimation.Comment: In Proceedings of CVPR 201
Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data
This paper presents a new method for shadow removal using unpaired data,
enabling us to avoid tedious annotations and obtain more diverse training
samples. However, directly employing adversarial learning and cycle-consistency
constraints is insufficient to learn the underlying relationship between the
shadow and shadow-free domains, since the mapping between shadow and
shadow-free images is not simply one-to-one. To address the problem, we
formulate Mask-ShadowGAN, a new deep framework that automatically learns to
produce a shadow mask from the input shadow image and then takes the mask to
guide the shadow generation via re-formulated cycle-consistency constraints.
Particularly, the framework simultaneously learns to produce shadow masks and
learns to remove shadows, to maximize the overall performance. Also, we
prepared an unpaired dataset for shadow removal and demonstrated the
effectiveness of Mask-ShadowGAN on various experiments, even it was trained on
unpaired data.Comment: Accepted to ICCV 201
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