• The Journal of Korea Robotics Society
• /
• v.4 no.4
• /
• pp.312-319
• /
• 2009

This paper proposes a low-complexity indoor localization method of mobile robot under the dynamic environment by fusing the landmark image information from an ordinary camera and the distance information from sensor nodes in an indoor environment, which is based on sensor network. Basically, the sensor network provides an effective method for the mobile robot to adapt to environmental changes and guides it across a geographical network area. To enhance the performance of localization, we used an ordinary CCD camera and the artificial landmarks, which are devised for self-localization. Experimental results show that the real-time localization of mobile robot can be achieved with robustness and accurateness using the proposed localization method.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.584-586
• /
• 2005

In this paper, low cost inertial sensor and compass were used instead of encoder for localization of mobile robot. Movements by encoder, movements by inertial sensor and movements by complementary filter with inertial sensor and compass were analyzed. Movement by complementary filter was worse than by only inertial sensor because of imperfection of compass. For the complementary filter to show best movements, compass need to be compensated for position error.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.2
• /
• pp.161-166
• /
• 2006

Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.

• Journal of Mechanical Science and Technology
• /
• v.15 no.10
• /
• pp.1369-1379
• /
• 2001

This paper focuses on a development of a sensor system measuring locations of a vehicle to localize a mobile robot while it tracks on the track (location sensor) . Also it focuses on a system configuration identifying the vehicle's orientation and distance from the object while it is stationary at certain station (position sensor) . As for the location sensor it consists of a set of sensors with a combined guiding and counting sensor, and an address-coded sensor to localize the vehicle while moving on the rail. For the position sensor a PSD (Position Sensitive Device) sensor with photo-switches sensor to measure the offset and orientation of the vehicle at each station is introduced. Both sensor systems are integrated with a microprocessor as a data relay to the main computer controlling the vehicle. The location sensor system is developed and its performance for a mobile robot is verified by experiments. The position measuring system is proposed and is robust to the environmental variation. Moreover, the two kinds of sensor systems guarantee a low cost application and high reliability.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1621-1623
• /
• 1997

Use of teaching pendant is the most widespread and economical way to teach desired motion to robots. It is also very primitive,time consuming and ineffective way of teaching which has not changed since the early days of robot. In order to reduce the teaching effor, a new efficient form of teaching is needed. Also, the recent robotics research trend into service robots such as home robot, nurse robot and medical robot calls for a new teaching method which is both easy and inexpensive. In this paper, the design and operation principle of a low cost force/moment sensor is presented. The proposed sensor architecture is so simple and inexpensive that it opens the prospect for a new paradigm of robot teaching which is easy and efficinet. Other prospective areas of application are tele-manipulation of robots wher it can be used in master arm, and virtual environment where it can be used as an user input device.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.6
• /
• pp.571-576
• /
• 2015

This paper proposes an auto-parking controller for omnidirectional mobile robots. The controller uses the multi-sensor system including ultrasonic sensor and camera. The several ultrasonic sensors of robot detect the distance between robot and each wall of the parking lot. The camera detects the global position of robot by capturing the image of artificial landmarks. To improve the accuracy of position estimation, we applied the extended Kalman filter with adaptive fuzzy controller. Also we developed the fuzzy control system to reduce the settling time of parking. The experimental results are presented to verify the usefulness of the proposed controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2005.11a
• /
• pp.179-184
• /
• 2005

Recently, studying on modeling the emotion of a robot has become issued among fields of a humanoid robot and an interaction of human and robot. Especially, modeling of the motivation, the emotion, the behavior, and so on, in the robot, is hard and need to make efforts to use our originality. In this paper, new modeling using mathematical formulations to represent the emotion and the behavior selection is proposed for the software robot with virtual sensor modules. Various Points which affect six emotional states such as happy or sad are formulated as simple exponential equations with various parameters. There are several experiments with seven external sensor inputs from virtual environment and human to evaluate this modeling.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.1
• /
• pp.37-42
• /
• 2006

Recently, studying on modeling the emotion of a robot has become issued among fields of a humanoid robot and an interaction of human and robot. Especially, modeling of the motivation, the emotion, the behavior. and so on, in the robot, is hard and need to make efforts to use ow originality. In this paper, new modeling using mathematical formulations to represent the emotion and the behavior selection is proposed for the software robot with virtual sensor modules. Various points which affect six emotional states such as happy or sad are formulated as simple exponential equations with various parameters. There are several experiments with seven external sensor inputs from virtual environment and human to evaluate this modeling.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.105.5-105
• /
• 2001

This paper describes a fuzzy steering controller for an autonomous mobile robot with MR sensor. Using the magnetic field(Bx, By, Bz) obtained from the MR sensor, we designed fuzzy controller for driving on the road center. Fuzzy rule base was built to magnetic field(Bx, By, Bz). To develop an autonomous mobile robot simulation program, we have done modeling MR sensor, dynamic model of mobile robot and coordinate transformation. A computer simulation of the robot including mobile robot dynamics and steering was used to verify the steering performance of the mobile robot controller using the fuzzy logic Good results were obtained by computer simulation. So, we confirmed the robustness of the proposed fuzzy controller by computer ...

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.4
• /
• pp.293-298
• /
• 2006

In this paper, a sensor fusion based robot navigation method for the autonomous control of a miniature human interaction robot is presented. The method of navigation blends the optimality of the Fuzzy Neural Network(FNN) based control algorithm with the capabilities in expressing knowledge and learning of the networked Intelligent Robotic Space(IRS). States of robot and IR space, for examples, the distance between the mobile robot and obstacles and the velocity of mobile robot, are used as the inputs of fuzzy logic controller. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a sensor fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process. Preliminary experiment and results are shown to demonstrate the merit of the introduced navigation control algorithm.