12,388 research outputs found
Real-time on-board obstacle avoidance for UAVs based on embedded stereo vision
In order to improve usability and safety, modern unmanned aerial vehicles
(UAVs) are equipped with sensors to monitor the environment, such as
laser-scanners and cameras. One important aspect in this monitoring process is
to detect obstacles in the flight path in order to avoid collisions. Since a
large number of consumer UAVs suffer from tight weight and power constraints,
our work focuses on obstacle avoidance based on a lightweight stereo camera
setup. We use disparity maps, which are computed from the camera images, to
locate obstacles and to automatically steer the UAV around them. For disparity
map computation we optimize the well-known semi-global matching (SGM) approach
for the deployment on an embedded FPGA. The disparity maps are then converted
into simpler representations, the so called U-/V-Maps, which are used for
obstacle detection. Obstacle avoidance is based on a reactive approach which
finds the shortest path around the obstacles as soon as they have a critical
distance to the UAV. One of the fundamental goals of our work was the reduction
of development costs by closing the gap between application development and
hardware optimization. Hence, we aimed at using high-level synthesis (HLS) for
porting our algorithms, which are written in C/C++, to the embedded FPGA. We
evaluated our implementation of the disparity estimation on the KITTI Stereo
2015 benchmark. The integrity of the overall realtime reactive obstacle
avoidance algorithm has been evaluated by using Hardware-in-the-Loop testing in
conjunction with two flight simulators.Comment: Accepted in the International Archives of the Photogrammetry, Remote
Sensing and Spatial Information Scienc
Development and demonstration of an on-board mission planner for helicopters
Mission management tasks can be distributed within a planning hierarchy, where each level of the hierarchy addresses a scope of action, and associated time scale or planning horizon, and requirements for plan generation response time. The current work is focused on the far-field planning subproblem, with a scope and planning horizon encompassing the entire mission and with a response time required to be about two minutes. The far-feld planning problem is posed as a constrained optimization problem and algorithms and structural organizations are proposed for the solution. Algorithms are implemented in a developmental environment, and performance is assessed with respect to optimality and feasibility for the intended application and in comparison with alternative algorithms. This is done for the three major components of far-field planning: goal planning, waypoint path planning, and timeline management. It appears feasible to meet performance requirements on a 10 Mips flyable processor (dedicated to far-field planning) using a heuristically-guided simulated annealing technique for the goal planner, a modified A* search for the waypoint path planner, and a speed scheduling technique developed for this project
Optimal Deployments of UAVs With Directional Antennas for a Power-Efficient Coverage
To provide a reliable wireless uplink for users in a given ground area, one
can deploy Unmanned Aerial Vehicles (UAVs) as base stations (BSs). In another
application, one can use UAVs to collect data from sensors on the ground. For a
power-efficient and scalable deployment of such flying BSs, directional
antennas can be utilized to efficiently cover arbitrary 2-D ground areas. We
consider a large-scale wireless path-loss model with a realistic
angle-dependent radiation pattern for the directional antennas. Based on such a
model, we determine the optimal 3-D deployment of N UAVs to minimize the
average transmit-power consumption of the users in a given target area. The
users are assumed to have identical transmitters with ideal omnidirectional
antennas and the UAVs have identical directional antennas with given half-power
beamwidth (HPBW) and symmetric radiation pattern along the vertical axis. For
uniformly distributed ground users, we show that the UAVs have to share a
common flight height in an optimal power-efficient deployment. We also derive
in closed-form the asymptotic optimal common flight height of UAVs in terms
of the area size, data-rate, bandwidth, HPBW, and path-loss exponent
Minimum noise impact aircraft trajectories
Numerical optimization is used to compute the optimum flight paths, based upon a parametric form that implicitly includes some of the problem restrictions. The other constraints are formulated as penalties in the cost function. Various aircraft on multiple trajectores (landing and takeoff) can be considered. The modular design employed allows for the substitution of alternate models of the population distribution, aircraft noise, flight paths, and annoyance, or for the addition of other features (e.g., fuel consumption) in the cost function. A reduction in the required amount of searching over local minima was achieved through use of the presence of statistical lateral dispersion in the flight paths
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