27,167 research outputs found
Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0
Within the context of Industry 4.0, mobile robot systems such as automated
guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major
areas challenging current communication and localization technologies. Due to
stringent requirements on latency and reliability, several of the existing
solutions are not capable of meeting the performance required by industrial
automation applications. Additionally, the disparity in types and applications
of unmanned vehicle (UV) calls for more flexible communication technologies in
order to address their specific requirements. In this paper, we propose several
use cases for UVs within the context of Industry 4.0 and consider their
respective requirements. We also identify wireless technologies that support
the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl
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
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