Home /Research /Localization on an Underwater Robot Using Monte Carlo Localization Algorithm
OTHER

Localization on an Underwater Robot Using Monte Carlo Localization Algorithm

Tae‐Gyun Kim, Nak-Yong Ko, Sung-Woo Noh, Young-Pil Lee

Year
2011
Citations
6

Abstract

The paper proposes a localization method of an underwater robot using Monte Carlo Localization(MCL) approach. Localization is one of the fundamental basics for autonomous navigation of an underwater robot. The proposed method resolves the problem of accumulation of position error which is fatal to dead reckoning method. It deals with uncertainty of the robot motion and uncertainty of sensor data in probabilistic approach. Especially, it can model the nonlinear motion transition and non Gaussian probabilistic sensor characteristics. In the paper, motion model is described using Euler angles to utilize the MCL algorithm for position estimation of an underwater robot. Motion model and sensor model are implemented and the performance of the proposed method is verified through simulation.

Keywords

UnderwaterMonte Carlo methodPosition (finance)RobotProbabilistic logicMonte Carlo localizationComputer scienceDead reckoningAlgorithmGaussian

Related papers

Browse all OTHER papers