• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1113-1116
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• 1999

For mobile robot, the navigation effectiveness can be improved by providing autonomy, but this autonomy requires the mobile robot to detect unknown obstacles and avoid collisions while moving it toward the target. This paper presents an effective method for autonomous navigation of the mobile robot in structured environments. This method uses ultrasonic sensor array to detect obstacles and utilizes force relationship between the obstacles and the target for avoiding collisions. Accuracy of sensory data produced by ultrasonic sensors is improved by employing error eliminating rapid ultrasonic firing (EERUF) technique. Navigation algorithm controlling both the velocity and steering simultaneously is developed, implemented to the mobile robot and tested on the floor filled with the cluttered obstacles. It is verified that from the results of the field tests the mobile robot can move at a maximum speed of 0.66 m/sec without any collisions.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.17-25
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• 2017

In this paper, we have implemented a low-cost mobile robot supporting the person tracking by detection using RGB-D cameras and ROS(Robot Operating System) framework. The mobile robot was developed based on the Kobuki mobile base equipped with 2's Kinect devices and a high performance controller. One kinect device was used to detect and track the single person among people in the constrained working area by combining point cloud data filtering & clustering, HOG classifier and Kalman Filter-based estimation successively, and the other to perform the SLAM-based navigation supported in ROS framework. In performance evaluation, the person tracking by detection was proved to be robustly executed in real-time, and the navigation function showed the accuracy with the mean distance error being lower than 50mm. The mobile robot implemented has a significance in using the open-source based, general-purpose and low-cost approach.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.105-110
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• 2009

In this paper, we proposed a navigation algorithm of the mobile robot for obstacle avoidance using a circular path planning method. The proposed method makes circular paths in order to avoid obstacles in the front side of the mobile robot. An optimal path for approaching to the target is selected and the linear and angular speeds for stable moving of the mobile robot are controlled. Obstacles are detected by image processing which reduce image data obtained from a web camera. Performance of the proposed algorithm is shown by experiments with application to the Pioneer-2DX mobile robot.

• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.178-186
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• 2011

Line tracking is a well defined method of mobile robot navigation. It is simple in concept, technically easy to implement, and already employed in many industrial sites. Among several different line tracking methods, magnetic sensing is widely used in practice. In comparison, vision-based tracking is less popular due mainly to its sensitivity to surrounding conditions such as brightness and floor characteristics although vision is the most powerful robotic sensing capability. In this paper, a vision-based robust path line detection technique is proposed for the navigation of a mobile robot assuming uncontrollable surrounding conditions. The technique proposed has four processing steps; color space transformation, pixel-level line sensing, block-level line sensing, and robot navigation control. This technique effectively uses hue and saturation color values in the line sensing so to be insensitive to the brightness variation. Line finding in block-level makes not only the technique immune from the error of line pixel detection but also the robot control easy. The proposed technique was tested with a real mobile robot and proved its effectiveness.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.2
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• pp.95-101
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• 2018

This paper presents a collision free mobile robot navigation based on the fuzzy inference fusion model in unkonown environments using multi-ultrasonic sensor. Six ultrasonic sensors are used for the collision avoidance approach where CCD camera sensors is used for the trajectory following approach. The fuzzy system is composed of three inputs which are the six distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot's wheels, and three cost functions for the robot's movement, direction, obstacle avoidance, and rotation. For the evaluation of the proposed algorithm, we performed real experiments with mobile robot with ultrasonic sensors. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.387-400
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• 2015

A fuzzy logic based mobile robot navigation system was developed to improve the driving ability without trapping inside obstacles in complex terrains, which is one of the most concerns in robot navigation in unknown terrains. The navigation system utilizes the data from ultrasonic sensors to recognize the distances from obstacles and the position information from a GPS sensor. The fuzzy navigation system has two groups of behavior rules, and the robot chooses one of them based on the information from sensors while navigating for the targets. In plain terrains the robot with the proposed algorithm uses one rule group consisting of behavior rules for avoiding obstacle, target steering, and following edge of obstacle. Once trap is detected the robot uses the other rule group consisting of behavior rules strengthened for following edge of obstacle. The output signals from navigation system control the speed of two wheels of the robot through the fuzzy logic data process. The test was conducted in the Matlab based mobile robot simulator developed in this study, and the results show that escaping ability from obstacle is improved.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.327-333
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• 2007

We propose a navigation algorithm using image-based visual servoing utilizing a fixed camera. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the image error between the goal position and the position of a mobile robot. The residual function which is the image error between the position of a mobile robot and the goal position is generally large for this navigation problem. So, this navigation problem can be considered as the nonlinear least squares problem for the large residual case. For large residual, we propose a method to find the second-order term using the secant approximation method. The performance was evaluated using the simulation.

• Journal of Power System Engineering
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• v.17 no.5
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• pp.112-120
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• 2013

In this study, we propose an improved view-based navigation method for obstacle avoidance and evaluate the effectiveness of the method in real environments with real obstacles. The proposed method possesses the ability to estimate the position and rotation of a mobile robot, even if the mobile robot strays from a recording path for the purpose of avoiding obstacles. In order to achieve this, ego-motion estimation was incorporated into the existing view-based navigation system. The ego-motion is calculated from SURF points between a current view and a recorded view using a Kinect sensor. In conventional view-based navigation systems, it is difficult to generate alternate paths to avoid obstacles. The proposed method is anticipated to allow a mobile robot greater flexibility in path planning to avoid humans and objects expected in real environments. Based on experiments performed in an indoor environment using a mobile robot, we evaluated the measurement accuracy of the proposed method, and confirmed its feasibility for robot navigation in museums and shopping mall.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.427-433
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• 2019

This paper propose a fuzzy inference model for map building and navigation for a mobile robot with an active camera, which is intelligently navigating to the goal location in unknown environments using sensor fusion, based on situational command using an active camera sensor. Active cameras provide a mobile robot with the capability to estimate and track feature images over a hallway field of view. In this paper, instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. Command fusion method is used to govern the robot navigation. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of active camera sensor for navigation experiments are fused into the identification process. Navigation performance improves on that achieved using fuzzy inference alone and shows significant advantages over command fusion techniques. Experimental evidences are provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the active camera and the feature images.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.