In this research, we propose a method of SLAM in a dynamic large outdoor environment using a laser scanner. Focus are cast on solving two major problems: 1) achieving global accuracy especially in non-cyclical environment, 2) tackling a mixture of data from both dynamic and static objects. Algorithms are developed, where GPS data and control inputs are used to diagnose pose error and guide to achieve a global accuracy; Classification of laser points and objects are conducted not in an independent module but across the processing in a framework of SLAM with moving object detection and tracking. Experiments are conducted using the data from two test-bed vehicles, and performance of the algorithms are demonstrated.
['Huijing Zhao', 'Masaki Chiba', 'Ryosuke Shibasaki', 'Xiaowei Shao', 'Jinshi Cui', 'Hongbin Zha']
SLAM in a dynamic large outdoor environment using a laser scanner