基于FastSLAM的绳系机器人同时定位与地图构建算法

doi:10.7527/S1000-6893.2020.23893

Abstract

Abstract: Tethered mobile robots can be used to explore extreme terrains such as steep slopes, cliffs, and gullies. During the exploration process, the tethers of the mobile robots will inevitably contact or even wrap around the obstacles. The classic FastSLAM framework does not apply to the Simultaneous Localization and Mapping (SLAM) of tethered robots due to the dependence of the contact points between the obstacles and the robots, and the nonlinearity of the robot model. In this paper, a modified FastSLAM-based algorithm is proposed to solve the SLAM problem of the tethered robot, where an unscented filter and a particle filter are adopted to estimate the positions of the contact points and the pose of the tethered robot, respectively. An unscented transformation on the nonlinear observation model is utilized to simplify the updating of the particle weights. Simulation results show that the proposed approach can effectively localize the contact points and improve the estimation performance of the robot pose.

Key words: mobile robots, extreme terrains, Simultaneous Localization and Mapping (SLAM), particle filters, unscented transformation

CLC Number:

V249.12

WANG Xiaotao, ZHANG Jiayou, WANG Xingbo, HAN Liangliang. Simultaneous localization and mapping algorithm based on FastSLAM framework for tethered robots[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(1): 523893-523893.

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Simultaneous localization and mapping algorithm based on FastSLAM framework for tethered robots

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