3-D object tracking through the use of a single camera and the motion of a driverless car
Typ
Examensarbete för masterexamen
Program
Complex adaptive systems (MPCAS), MSc
Publicerad
2021
Författare
Ovnell, Andreas
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
There has been a very large increase in interest and development of partially or fully
driverless cars in recent years. For these driverless cars to function, they need to
be able to navigate to their destination while avoiding nearby objects. This can be
done using simultaneous localisation and mapping (SLAM). SLAM is the task of
simultaneously creating a map of the surrounding objects while keeping track of the
car’s position within this map. This thesis will look into the feasibility of using a
single camera attached on a driverless car to perform SLAM on cones detected by
the real-time object detection system You only look once (YOLO).
Three different methods were tested. All of these require a calibrated camera that is
capable of determining horizontal and vertical angles from the pixel positions. The
first ‘triangulation’ method uses that the distance travelled and rotation between
two frames is known. The second ‘plane projection’ method is an optimisation problem
which consists of finding the variables which result in lowest error, and through
this determine the cone distances and car speed. The map of the surrounding cones
is moved according to the estimated velocity and rotation of the car such that the
car is always placed at the origin, allowing for use of multiple detections to improve
accuracy. The third ‘distance from cone height’ method works by using the size of
the cone detections in order to determine the approximate distance of each cone,
use this to determine the approximate angle of the camera and then use the median
angle to make the final distance estimates.
The triangulation method was shown to be completely unsuitable for mono-camera
use. The plane projection method was shown to be unreliable, likely due to a relatively
small number of visible cones and a too large noise amplitude of detections
from YOLO. The distance from cone height method was shown to be the best out of
the tested methods, as it was simple, fast and quite reliable. However, this method
still had an error approximately 1.4 times larger than what is advertised by commercial
stereo camera systems.
Beskrivning
Ämne/nyckelord
SLAM , driverless , autonomous , depth vision , 3D , mono camera