Authors:
Anand Abhishek
and
K. S. Venkatesh
Affiliation:
IIT Kanpur, India
Keyword(s):
Implicit Extended Kalman Filter, UAV, Autonomous Navigation, Epipolar Constraint, IMU, Planar Constraint.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
;
Pattern Recognition
;
Robotics
;
Software Engineering
;
Tracking and Visual Navigation
Abstract:
Unmanned aerial vehicle(UAV) are widely used for commercial and military purposes. Various computer
vision based methodologies are used for aid in autonomous navigation. We have presented an implicit extended
square root Kalman filter based approach to estimate the states of an UAV using only onboard camera which
can be either used alone or assimilated with the IMU output to enable reliable, accurate and robust navigation.
Onboard camera present information rich sensor alternative for obtaining useful information form the craft,
with the added benefits of being light weight, small and no extra payload. The craft system model is based on
differential epipolar constraint with planar constraint assuming the scene is slowly moving. The optimal state
is then estimated using current measurement and defined the system model. Pitch and roll is also estimated
from above formulations. The algorithms results are compared with real time data collected from the IMU.