• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.473-478
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• 1992

This paper aims to investigate the navigation control of a mobile robot in a confined environment. Steering angle becomes control variable which is computed from the fuzzy control rules. The identification method proposed in this paper presents the fuzzy control rules obtained through modelling of. the driving actions of human operator. The feasibility of the proposed method is evaluated through the application of the identified fuzzy controls rules to the navigation control of a mobile robot which follows the center of a corridor.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.75-75
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• 2000

Recently, number of navigation system using GPS and other complementary sensors has been developed to offer high-position accuracy. In this paper, an integration of GPS and Dead-Reckoning, which consists of a fiber optical gyroscope and two high-precision wheel-motor encoders for a unmanned navigation system, is presented. The main objective of this integrated GPS/DR unmanned navigation system is to provide accurate position and heading navigation data continuously for autonomous mobile robot. We propose a method for increasing the accuracy of the estimated position of the mobile robot by its DR sensors, high-precision wheel-motor encoders and a fiber optical gyroscope. We used Kalman filter theory to combine GPS and DR measurements. The performance of GPS/DR navigation system is evaluated.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.713-716
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• 1991

This paper describes a methodology of mobile robot navigation which is designed to carry heavy payloads at high speeds to be used in FMS(Flexible Manufacturing System) without human control. Intelligent control scheme using fuzzy logic is applied to the navigation control. It analyzes sensor readings from multi-sensor system, which is composed of ultrasonic sensors, infrared sensors and odometer, for environment learning, planning, landmark detecting and system control. And it is implemented on a physical robot, AGV(Autonomous Guided Vehicle) which is a two-wheeled, indoor robot. An on-board control software is composed of two subsystems, i.e., AGV control subsystem and Sensor control subsystem. The results show that the navigation of the AGV is robust and flexible, and a real-time control is possible.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2142-2148
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• 2015

This paper proposes novel real-time footstep planning and following methods for the navigation of humanoid robots. A footstep command is defined by a walking direction and step lengths for footstep planning. The walking direction is determined by a uni-vector field navigation method, and the allowable yawing range caused by hardware limitation is considered. The lateral step length is determined to avoid collisions between the two legs while walking. The sagittal step length is modified by a binary search algorithm when collision occurs between the robot body and obstacles in a narrow space. If the robot body still collides with obstacles despite the modification of the sagittal step length, the lateral step length is shifted at the next footstep. For footstep following, a walking pattern generator based on a 3-D linear inverted pendulum model is utilized, which can generate modifiable walking patterns using the zero-moment point variation scheme. Therefore, it enables a humanoid robot to follow the footstep command planned for each footstep. The effectiveness of the proposed method is verified through simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.990-994
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• 1999

This paper proposes a new fuzzy-neural algorithm for navigation of a mobile robot with stationary and moving obstacles environment. The proposed algorithm uses fuzzy algorithm for its speed control and neuralnetwork for effective collision avoidance. Some computer simulation results for a mobile robot equipped with ultrasonic range sensors show that the suggested navigation algorithm is very effective to escape in stationary and moving obstacles environment.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2015-2018
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• 2005

Obstacle avoidance is a basic skill to make a mobile robot move effectively and safely even in any arbitrarily given environment. Because of the difficulty of self-location caused by unavoidable slip and drift errors of sensors and effective detection of any encountered obstacle, only finite and simple obstacle avoidance strategies can be carried out. In this paper we mainly explored how to make a robot perform effectively obstacle detection and avoidance in the guideline navigation with one CCD video camera and some supersonic sensors. Making use of the specially designed guideline, the detection and calculation of the geometric dimensions of the encountered obstacle became simpler. And possible avoidance strategies appropriate to our navigation were studied and the simulations results were given.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.385-389
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• 2009

This paper deals with the enhancement of the complex potential navigation for wheeled mobile robots. The circle theorem from complex function theory is used to avoid an obstacle, and the enhancement to avoid multiple obstacles is proposed. The limit cycle navigation can be combined for robot to kick the ball to the intentioned direction. Avoiding step and superposing twin vortices can be applied to adjust the direction of robot's trajectory. The proposed method is verified through a set of simulation works, and the feasibilities for the enhancement of complex potential theory are successful.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.3-129
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• 2001

In this paper, a novel navigation method is presented for the cleaning robot in the unknown workspace. In order to do this, we propose a new map representation method and a complete coverage navigation method. First, we discuss a triangular cell map representation which makes the cleaning robot navigate with shorter path and increased flexibility than a rectangular cell map representation. Then we proposed a complete coverage navigation and map construction method which the cleaning robot can navigate the complete workspace although it has perfectly no information about environment. Finally, we evaluate the performance of our proposed triangular cell map comparing to that of the rectangular cell map via the existing ...

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.203-209
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• 2010

This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.117-124
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• 2006

In this paper, we develope the navigation system for patrol robots in indoor environment. The proposed system consists of PDA map modelling, a localization algorithm based on a global position sensor and an automatic charging station. For the practical use in security system, the PDA is used to build object map on the given indoor map. And the builded map is downloaded to the mobile robot and used in path planning. The global path planning is performed with a localization sensor and the downloaded map. As a main controller, we use PXA270 based hardware platform in which embedded linux 2.6 is developed. Data handling for various sensors and the localization algorithm are performed in the linux platform. Also, we implemented a local path planning algorithm for object avoidance with ultra sonar sensors. Finally, for the automatic charging, we use an infrared ray system and develop a docking algorithm. The navigation system is experimented with the two-wheeled mobile robot using North-Star localization system.