Abstract:
This paper proposes a simulation method to select autonomously the stable visual landmarks from the
observed features by stereo measurement and to establish the 3D obstacle map. Due to the
measurement and motion error of the robot, the observed posture positions include the uncertainty.
In this paper, we discuss the simultaneous stereo type localization and map building (SLAM)
problems. SLAM problem asks if it is possible for an autonomous robot to start in an unknown
location in an unknown environment and then to incrementally build a map of this environment while
simultaneously using this map to compute the absolute robot location. From the results, we prove that
a solution to the SLAM problem is indeed possible for 3D obstacle map. This implementation is used
to demonstrate how some key issues such as map management and data association can be handled in
a practical environment.
