Tracking and data association
Estimating uncertain spatial relationships in robotics
Autonomous robot vehicles
Modeling a dynamic environment using a Bayesian multiple hypothesis approach
Artificial Intelligence
A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots
Machine Learning - Special issue on learning in autonomous robots
Directed Sonar Sensing for Mobile Robot Navigation
Directed Sonar Sensing for Mobile Robot Navigation
An Experimental and Theoretical Investigation into Simultaneous Localisation and Map Building
The Sixth International Symposium on Experimental Robotics VI
Simultaneous stochastic mapping and localization
Simultaneous stochastic mapping and localization
Robocentric map joining: Improving the consistency of EKF-SLAM
Robotics and Autonomous Systems
Line Extraction from Mechanically Scanned Imaging Sonar
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
A sonar data processing system of underwater robot based on C6000 DSP
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1
Scan matching SLAM in underwater environments
Autonomous Robots
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This paper investigates the problem of concurrent mapping and localization (CML) using forward look sonar data. Results are presented from processing of an oceanic data set from an 87 kHz US Navy forward look imaging sonar using the stochastic mapping method for CML. The goal is to detect objects on the seabed, map their locations, and concurrently compute an improved trajectory for the vehicle. The resulting trajectory is compared with position estimates computed with an inertial navigation system and Doppler velocity sonar. The results demonstrate the potential of concurrent mapping and localization algorithms to satisfy the navigation requirements of undersea vehicles equipped with forward look sonar.