Kyoung-sig Roh

Experiments on decision making strategies for a lane departure warning system

Describes two decision making strategies of the lane departure warning system for a vehicle and provides experimental results to assess the performance of each strategy. The overview of the lane departure warning system mounted on the vehicle is presented. A lateral offset (LO) based strategy and a time to lane crossing (TLC) based strategy are proposed to be used in the warning module which detects unintended lane departure so as to warn the driver. The performance criteria of the warning strategies are defined as: 1) false alarm rate, 2) alarm triggering time. The proposed strategies are incorporated in our lane departure warning system to be tested in real expressway experiments. The experimental results for the performance optimization of both strategies are discussed and compared with each other.

Self-localization of a mobile robot without camera calibration using projective invariants

In this paper, we propose a visual-based self-localization algorithm of an indoor mobile robot. The algorithm does not require calibration and can be worked with only a single image by using the projective invariant relationship between natural landmarks. The position of the robot is determined by relative positioning. Also, the method does not require previous information of the position of the robot. The robustness and feasibility of our algorithm have been demonstrated through experiments in hallway environments.