Young-Ho Choi

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This paper describes a geometrically constrained Extended Kalman Filter (EKF) framework for a line feature based SLAM, which is applicable to a rectangular indoor environment. Its focus is on how to handle sparse and noisy sensor data, such as PSD infrared sensors with limited range and limited number, in order to develop a low-cost navigation system. It(More)
This paper presents a sensor-based online coverage path planning algorithm guaranteeing a complete coverage of unstructured planar environments by a mobile robot. The proposed complete coverage algorithm abstracts the environment as a union of robot-sized cells and then uses a spiral filling rule. It can be largely classified as an approximate cellular(More)
In Location-Based Services (LBSs), users send location-based queries to LBS servers along with their exact locations, but the location information of the users can be misused by adversaries. For this, a mechanism to deal with the users’ privacy protection is required. In this paper, we propose a new cloaking algorithm for privacy protection in LBSs.(More)
This paper presents an on-line complete-coverage path planning algorithm for mobile robots based on approximate cellular decomposition, which abstracts the target environment using grid. Most existing grid-based coverage algorithms have a common problem of constrained mobility which degrades the efficiency of the coverage task by inducing zigzag like path.(More)
This paper presents a novel real-time SLAM method working in an unstructured indoor environment with a single forward viewing camera. Most existing visual SLAM methods extract features from the environment, associate them in different images and produce a feature map as a result. However, our approach estimates the distances between the robot and the(More)