Sentence examples for localisation algorithm from inspiring English sources

In this paper, a novel target acquisition and localisation algorithm (TALA) is introduced that offers a capability for detecting and localising multiple targets using the intermittent "signals-of-opportunity" (e.g. acoustic impulses or radio frequency transmissions) they generate.

In this paper, a novel target acquisition and localisation algorithm (TALA) has been introduced that offers a capability for detecting and localising an unknown number of targets using the intermittent "signals-of-opportunity" they generate (e.g. "events" such as acoustic impulses or radio frequency transmissions).

The localisation algorithm was validated using simulation of the robotic platform and using visual odometry based on real field video data.

The CRLB provides a bound on the performance of any unbiased target localisation algorithm.

In Fig. 2 d, the final outputs of the target localisation algorithm are shown for the exemplar scenario.

The target acquisition and localisation algorithm (TALA) introduced herein addresses the complex multi-sensor/multi-target data association problem, in order to detect and localise an unknown number of target signals/events (e.g. such as acoustic impulses generated by artillery firings or intermittent radio frequency transmissions).

To control for subjectivity in the manual scoring process, we used a co-localisation algorithm (Aperio) to impartially examine Msx2 expression and localisation.

Application of the Simultaneous Localisation and Mapping algorithm are shown using data collected by the vehicle operating on the Great Barrier Reef in Australia.

To control for the subjectivity inherent in the manual scoring process, we utilised a co-localisation image analysis algorithm (Aperio Technologies) to further examine Msx2 localisation and expression.

The simultaneous localisation and mapping (SLAM) algorithm has drawn increasing interests in autonomous robotic systems.

The simultaneous localisation and mapping (SLAM) algorithm has been developed to meet the challenge of building and updating a map of the surroundings in moving mobile robots, which includes mapping robots poses without prior knowledge of their surroundings.