Simultaneous localization and mapping for tethered robot based on UFastSLAM

Abstract

The tethered mobile robot can be used to detect extreme terrain. During the movement, it will inevitably contact or even entangle with obstacles. In this paper, a simultaneous localization and mapping (SLAM) algorithm for tethered robots based on the UFastSLAM framework is proposed, which uses particle filtering and unscented transformation to estimate the pose of the tethered robot and the positions of the anchor points. The simulation results show that the algorithm can effectively estimate the position of anchor points and improve the performance of robot pose estimation simultaneously.