A study on Unscented SLAM with path planning algorithm integration

Abstract

This paper considers a framework of Unscented SLAM in integration with A∗ algorithm to build a map of an unknown environment and guide the robot to reach a prescribed destination so that the robot is able to become truly autonomous. In Simultaneous Localization and Mapping problem (SLAM), the use of Unscented Kalman Filter (UKF) aims at reducing the disadvantages as a result of linearization in the typical Extended Kalman Filter (EKF) approach. When the map is available, to provide the robot an ability to navigate in its environment, A∗ path planning algorithm will be applied to direct the robot to the desired goal by finding an appropriate path between starting point and destination. Simulation tests are executed to illustrate the performance of this framework.