6TH International Congress on Technology - Engineering - Kuala Lumpur3 - Malaysia (2018-07-19)

Improvement Of Robot Localization And Mapping Using Local Mapping

This study presents a vision-assisted robot navigation system. The major objective of the system is to assist the robot implementing the tasks of localization and mapping in the environment where the global positioning system (GPS) is denied. The visual sensor provided measurement data for estimating the robot state and building the environment map. The position of the landmarks was initialized using the non-standard stereo geometry method (non-SSG). The states of robot and static objects were recursively predicted and estimated using the extended Kalman filter. When the range of the environment map was too large, the computation time increased dramatically. Real-time implementation of robot visual navigation became an impossible task. To improve the problem, the concept of local map was proposed in this study. The sizes of the state and covariance vectors were limited in order to reduce the computation time. The software program of the robot navigation system was developed in a PC-based controller using Microsoft Visual Studio C++. The navigation system integrated the sensor inputs, image processing, and state estimation. The resultant system was used to perform the tasks of simultaneous localization and mapping (SLAM) for large environments.
Wei-Kai Wang, Yin-Tien Wang