Abstract

This work presents a solution to the Simultaneous Localization and Mapping (SLAM) problem of Unmanned Ground Vehicle (UGV) supported by a stereovision camera. There are many ways to approach this problem, mostly based on the sequential probabilistic process. The EKF-SLAM algorithm is one popular solution based on Extended Kalman Filter (EKF) to solve this problem that struggles with Jacobians’ calculation. FAST-SLAM is another popular algorithm based on the Rao-Blackwellized particle filter that has issues with real-time implementation. As a means to ameliorate the SLAM solution limitations, especially when the process and observation models contain uncertain parameters, a new adaptive Boundary Layer With algorithm based on the Smooth Variable Structure Filter (ASVSF) is proposed to solve the UGV visual SLAM problem. Hence, the adaptive SVSF-SLAM algorithm is proposed with an original formulation. This algorithm was implemented on Pioneer 3-AT mobile robot, using a stereo vision sensor in 3D. Simulation results show efficiency and give an advantage face modeling uncertainties and noises and it has significantly improved the performance of the estimation process.

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