Efficient Non-Odometry Method for Environment Mapping and Localisation of Mobile Robots

Abstract

The paper presents the simple algorithm of simultaneous localisation and mapping (SLAM) without odometry information. The proposed algorithm is based only on scanning laser range finder. The theoretical foundations of the proposed method are presented. The most important element of the work is the experimental research. The research underlying the paper encompasses several tests, which were carried out to build the environment map to be navigated by the mobile robot in conjunction with the trajectory planning algorithm and obstacle avoidance.

Research on Path Planning Algorithm for Driverless Vehicles

“…In the unmanned path planning, the bidirectional RRT is used for sampling and exploration from the target position and the starting point at the same time, and the separation law is added to the collision detection to improve the planning efficiency [8]. In the RRT algorithm, the adaptive is added to reduce the randomness of the sampling, and the ap-propriate node is selected by using the relationship between the angle and the distance, and the path is optimized [9,10]. The RRT algorithm is used to help the artificial potential field method escape the local minimum trap, but the path oscillation still cannot be solved and the randomness of the selected virtual target point position is too large, which affects the efficiency of path planning [11].…”