Airborne simultaneous localisation and map building
JH Kim, S Sukkarieh - … on Robotics and Automation (Cat. No …, 2003 - ieeexplore.ieee.org
2003 IEEE International Conference on Robotics and Automation (Cat …, 2003•ieeexplore.ieee.org
This paper presents results of the application of simultaneous localisation and map building
(SLAM) for an uninhabited aerial vehicle (UAV). Single vision camera and inertial
measurement unit (IMU) are installed in a UAV platform. The data taken from a flight test is
used to run the SLAM algorithm. Results show that both the map and the vehicle uncertainty
are corrected even though the model of the system and observation are highly non-linear.
The results, however, also indicate that further work of observability and the relationship …
(SLAM) for an uninhabited aerial vehicle (UAV). Single vision camera and inertial
measurement unit (IMU) are installed in a UAV platform. The data taken from a flight test is
used to run the SLAM algorithm. Results show that both the map and the vehicle uncertainty
are corrected even though the model of the system and observation are highly non-linear.
The results, however, also indicate that further work of observability and the relationship …
This paper presents results of the application of simultaneous localisation and map building (SLAM) for an uninhabited aerial vehicle (UAV). Single vision camera and inertial measurement unit (IMU) are installed in a UAV platform. The data taken from a flight test is used to run the SLAM algorithm. Results show that both the map and the vehicle uncertainty are corrected even though the model of the system and observation are highly non-linear. The results, however, also indicate that further work of observability and the relationship between vehicle model drift and the number and the location of landmarks need to be further analysed given the highly dynamic nature of the system.
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