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Indoor localization is essential technology in service robot market. To localize the position of robot, laser scanner is widely used. But it has limit that laser scanner has probability return unexpected data when the space that the robot operate is too crowded. In this dynamic environment, the robot needs another sensor to complement weakness of laser scanner. This paper proposes vision sensor for complement sensor. But previous works that use vision sensor need many computational tasks. So this paper proposes the way to uses vision marker. This method makes the robot executing localization with efficiency. This algorithm applied on the robot platform and experiment show this algorithm is valid in dynamic and static environment. [ABSTRACT FROM PUBLISHER]

We propose the modified dynamic window approach for indoor transport robot. The dynamic window approach is the popular collision avoidance algorithm that considers the heading direction of the robot, the distance to the obstacle, and the velocity of the robot. The objective function of the DWA thinks faster speed is better but it is very dangerous when there are many people around. They will feel discomfort with fast vehicle around them. This paper proposes that when the robot is in crowded place which means there are many dynamic obstacles around the robot, the robot move slow down to watch out the collision with them. It is implemented by using several fuzzy rules to determine the possible actions of the robot in DWA. Experiment results are given to validate our proposed method. [ABSTRACT FROM PUBLISHER]