• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.11
• /
• pp.1139-1145
• /
• 2008

A robust position sensing system is proposed in this paper for a ubiquitous mobile robot which moves indoors as well as outdoors. The Differential GPS (DGPS) which has a position estimation error of less than 5 m is a general solution when the mobile robot is moving outdoor, while an active beacon system (ABS) with embedded ultrasonic sensors is reliable as an indoor positioning system. The switching from the outdoor to indoor or vice versa causes unstable measurements on account of the reference coordinates and algorithm changes. To minimize the switching time in the position estimation and to stabilize the measurement, a robust position sensing system is proposed. In the system, to minimize the switching delay, the door positions are stored and updated in a database. Using the database, the approaching status of the mobile robot from indoor to outdoor or vice versa has been checked and the switching conditions are prepared before the mobile robot actually moves out or moves into the door. The reliability and accuracy of the robust positioning system based on DGPS and ABS are verified and demonstrated through the real experiments using a mobile robot prepared for this research.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.2
• /
• pp.75-82
• /
• 2016

Visible light communication (VLC) using LED lamps is suitable for implementing an indoor positioning system in an indoor environment where the global positioning system (GPS) signal does not reach. In this paper, we present an indoor positioning system for mobile robots using a VLC beacon and fuzzy rules. This system consists of an autonomous mobile robot, VLC modules, and device application software. Fuzzy rules are applied to plan the global and local paths along which the mobile robot navigates indoors. The VLC transmitter modules are attached to the wall or the ceiling as beacons to transmit their own location information. The variable pulse position modulation (VPPM) algorithm is used to transmit data, which is a new modulation scheme for VLC providing a dimming control mechanism for flicker-free optical communication. The mobile robot has a receiver module to receive the location information while performing its mission in the environment where VLC transmitters are deployed.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.54 no.6
• /
• pp.366-371
• /
• 2005

For an autonomous mobile robot localization, it is very important for the robot to be able to recognize indoor environment and match a detected object to an object defined within a map developed either online or of offline. Given the map defining the locations of geometric beacons like wall and corner existing in the robot operation environment, this paper presents a stereo ultrasonic sensor based method practically applicable in recognizing the geometric beacons in real-time. The stereo ultrasonic sensor used in the experiment consists of an ultrasonic transmitter and two ultrasonic receivers placed symmetrically about the transmitter Experimental results are provided to demonstrate that the proposed method is more efficient in recognizing wall and coner than the conventional method of using multiple number of transmitter-receiver pairs.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.8
• /
• pp.804-809
• /
• 2007

Initialization problem is defined for indoor mobile robot as a whole process from arrival to normal operation in a new environment. The unstructured environment make the process much more difficult compared to industrial robot in structured environments. We propose a simple and efficient initialization process based on artificial stars on ceiling. Important task points and paths connecting task points are defined based on the corresponding artificial stars. This approach can be used for all kinds of indoor mobile robots with landmarks used for indoor localization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.449-452
• /
• 2007

An intelligent robot with RSSI based indoor location estimation function was designed and implemented. A wireless sensor node was attached to the robot to received the location data from the indoor location estimation function. Spartan III was used as the main control device in the mobile robot. The current location data collected from the indoor location estimation system was transferred to the mobile robot and server through Zigbee/IEEE 802.15.4 wireless communication of the sensor node. Once the location data is received, the sensor node senses the direction of the robot head and directs the robot to move to its destination. Indoor location estimation intelligent robot is able to move efficiently and actively to the user appointed location by implementing the proposed obstacles avoidance algorithm. This system is able to monitor real-time environmental data and location of the robot using PC program. Indoor location estimation intelligent robot also can be controlled by executing the instructions sent from the PC program.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.20 no.2
• /
• pp.133-138
• /
• 2011

RFID system can be used to improve object recognition, map building and localization for robot area. A novel method of indoor navigation system for a mobile robot is proposed using RFID technology. The mobile robot With a RFID reader and antenna is able to find what obstacles are located where in circumstance and can build the map similar to indoor circumstance by combining RFID information and distance data obtained from sensors. Using the map obtained, the mobile robot can avoid obstacles and finally reach the desired goal by $A^*$ algorithm. 3D map which has the advantage of robot navigation and manipulation is able to be built using z dimension of products. The proposed robot navigation system is proved to apply for SLAM and path planning in unknown circumstance through numerous experiments.

• The Journal of Korea Robotics Society
• /
• v.6 no.1
• /
• pp.58-68
• /
• 2011

This paper proposes a technique of indoor localization for mobile robot by so called indoor GPS and EKF. Basically the concept of indoor GPS is similar outdoor GPS, and the indoor GPS gets distances between Anchors and Tag by a ranging method of CSS and then estimates the coordinate by distances and known Anchor positions. After we performed performance test of indoor GPS system in ideal and multipath environment, we configured that the indoor GPS has internal error factors and external error factors. This paper handled a multipath problem belonging to external error factors. At first various direct physical method are introduced to fix the multipath problems, and as expected we got errors corrected considerably. And then the method of selective anchors for indoor GPS is applied. With these two level improvement of indoor GPS performance, EKF(Extended Kalman Filter) is applied to mobile robot in indoor environment. The usefulness of the proposed methods are shown by a series of experiments in a environment giving contaminated data by multipath.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.4
• /
• pp.301-306
• /
• 2016

This paper presents the results of a study for robust self-localization and indoor slam using external cameras (such as a CCTV) and odometry of mobile robot. First, a position of mobile robot was estimated by using maker and odometry. This data was then fused with camera data and odometry data using an extended kalman filter. Finally, indoor slam was realized by applying the proposed method. This was demonstrated in the actual experiment.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.973-978
• /
• 2005

In this paper, we investigate an improved mobile robot localization method using Kalman filter. The highlight of the paper lies in the formulation of combined Kalman filter and its application to mobile robot experiment. The combined Kalman filter is a kind of extended Kalman filter which has an extra degree of freedom in Kalman filtering recursion. It consists of the standard Kalman filter, i.e., the predictor-corrector and the perturbation estimator which reconstructs unknown dynamics in the state transition equation of mobile robot. The combined Kalman filter (CKF) enables to achieve robust localization performance of mobile robot in spite of heavy perturbation such as wheel slip and doorsill crossover which results in large odometric errors. Intrinsically, it has the property of integrating the innovation in Kalman filtering, i.e., the difference between measurement and predicted measurement and thus it is so much advantageous in compensating uncertainties which has not been reflected in the state transition model of mobile robot. After formulation of the CKF recursion equation, we show how the design parameters can be determined and how much beneficial it is through simulation and experiment for a two-wheeled mobile robot under indoor GPS measurement system composed of four ultrasonic satellites. In addition, we discuss what should be considered and what prerequisites are needed to successfully apply the proposed CKF in mobile robot localization.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.6
• /
• pp.529-536
• /
• 2004

Autonomous navigation of an indoor mobile robot using the global ultrasonic system is presented in this paper. Since the trajectory error of the dead-reckoning navigation grows with time and distance, the autonomous navigation of a mobile robot requires to localize the current position of the robot, so that to compensate the trajectory error. The global ultrasonic system consisting of four ultrasonic generators fixed at a priori known positions in the work space and two receivers on the mobile robot has the similar structure with the well-known satellite GPS(Global Positioning System), and it is useful for the self-localization of an indoor mobile robot. The EKF(Extended Kalman Filter) algorithm for the self-localization is proposed and the autonomous navigation based on the self-localization is verified by experiments.