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Details von Development of an obstacle detection mechanism for the autonomous oTToCar model car
Typ
Teamprojekt
Beschreibung
One of the current developments in the automotive domain is automated driving. The
automotive companies promise increased comfort for the passengers and the driver as well
as reduced emissions. However, these technologies need to be developed and integrated
into the cars that needs competent personal. Therefore, the institute of automotive
computer science of the University of Braunschweig started together with some industrial
partners the Carolo Cup. The cup provides students with the opportunity to develop,
test and enhance technologies of automated driving in a smaller scale. To participate in
the cup, a team, consisting purely of students, needs to develop and build a 1:10 scale
model car, which is able to drive autonomously on a static track. The track consists of
straights, curves and crossings with and partially without markings. Additionally the
car needs to be able to avoid obstacles on the track and park itself.
Since 2013 the Otto-von-Guericke University has its own Carolo Cup team, the oTToCar
Team[2]. The team achieved a 2nd rank in the junior cup in 2014 and aims for the senior
cup in 2015. Currently, the car is able to follow the track autonomously and find and
drive itself in parking slots. However, there are no means to detect obstacles on the road
and avoid them.
This team project aims to provide the car with a robust obstacle detection that may be
used by other components of the car. The components of the car are linked using the
Robotic Operating System (ROS) and heavily use the existing frameworks of ROS like
the OpenCV (Open Computer Vision). As a result of the project an obstacle detection
component shall be implemented that is able to detect the obstacles on the road as
defined by the rules of the Carolo cup and provide the current road condition via ROS
to other components like lane following and automated parking. The currently available
hardware on the car are a Hokuyo Laser scanner, some infrared distance sensors, an
odometer, an IMU and an industrial camera.
Betreuer
Christoph Steup
Student
Chris Long
Status
in Arbeit
verteidigt am
15. August 2018
Download
 oTToCar-Obstacle.pdf