• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.246-257
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• 2010

Autonomous guided robot navigation which consists of following unknown paths and avoiding unknown obstacles has been a fundamental technique for unmanned robots in outdoor environments. The unknown path following requires techniques such as path recognition, path planning, and robot pose estimation. In this paper, we propose a novel sensor fusion system for autonomous guided robot navigation in outdoor environments. The proposed system consists of three monocular cameras and an array of nine infrared range sensors. The two cameras equipped on the robot's right and left sides are used to recognize unknown paths and estimate relative robot pose on these paths through bayesian sensor fusion method, and the other camera equipped at the front of the robot is used to recognize abrupt curves and unknown obstacles. The infrared range sensor array is used to improve the robustness of obstacle avoidance. The forward camera and the infrared range sensor array are fused through rule-based method for obstacle avoidance. Experiments in outdoor environments show the mobile robot with the proposed sensor fusion system performed successfully real-time autonomous guided navigation.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.58-67
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• 1995

A path planning algorithm using a laser range finder are presented for real-tiem navigation of an autonomous guided vehicle. Considering that the laser range finder has the excellent resolution with respect to angular and distance measurements, a sophisticated local path planning algorithm is achieved by using the human's heuristic method. In the case of which the man knows not rhe path, but the goal direction, the man forwards to the goal direction, avoids obstacle if it appears, and selects the best pathway when there are multi-passable ways between objects. These heuristic principles are applied to the path decision of autonomous guided vehicle such as forward open, side open and no way. Also, the effectiveness of the established path planning algorithm is estimated by computer simulation in complex environment.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1113-1114
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• 1996

We describe an algorithm to control an autonomous guided vehicle with 2-diagonal driving wheels, which navigates in the clean room.

• Journal of Navigation and Port Research
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• v.28 no.7
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• pp.635-640
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• 2004

In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) operating in container terminals is presented. The developed navigation algorithm takes the form of a federated information filter used to detect other AGVs and avoid obstacles using fused information from multiple sensors. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. It is proved that the information state and the information matrix of the suggested filter, which are weighted in terms of an information sharing factor, are equal to those of a centralized information filter under the regular conditions. Numerical examples using Monte Carlo simulation are provided to compare the centralized information filter and the proposed one.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.459-464
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• 2004

In this paper, an autonomous navigation system for autonomous guided vehicles (AGVs) operated in an automated container terminal is designed. The navigation system is based on the sensors detecting the range and bearing. The navigation algorithm used is an interacting multiple model (IMM) algorithm to detect other AGVs and avoid other obstacles using informations obtained from multiple sensors. As models to detect other AGVs (or obstacles), two kinematic models are derived： Constant velocity model for linear motion and constant speed turn model for curvilinear motion. For constant speed turn model, an unscented Kalman filter (UKF) is used because of drawbacks of the extended Kalman filter (EKF) in nonlinear system. The suggested algorithm reduces the root mean squares error for linear motions, while it can rapidly detect possible turning motions.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.648-654
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• 2010

In this paper, a navigation system was designed, and performance tested in order to confirm the safety improvement of the GNSS(Global Navigation Satellite System)-based AGV(Autonomous Guided Vehicle) which used only position information on of GNSS. We developed DR(Dead Reckoning) navigation system that involve the use of GNSS abnormal positoning error detection and GNSS signal outage. The test results show that GNSS positioning error is detection can be archived with an error of more than 0.15m. In addition, the DR driving position error is 1.5m for an 8s GNSS positioning service outage.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.180-187
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• 2010

In this paper, a GNSS-based AGV system was designed, and steering tested on a golf cart using electric wires in order to confirm the control efficiency of the low speed vehicle which used only position information of GNSS. After analyzed the existing AGVs system, we developed controller and steering algorithm using GNSS based position information. To analyze the performance of the developed controller and steering algorithm, straight-type and circle-type trajectory test are executed. The results show that steering performance of GNSS-based AGV system is ${\pm}\;0.2m$ for a reference trajectory.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1071-1084
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• 1992

In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.343-353
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• 1995

The path navigation of autonomous guided vehicle(AGV) or autonomous mobile robot(AMR) assumed that the environment was completely known and the obstacles were fixed. So that, in an environment only partly known or not known at all, the previous works were not successful since the path exploration techniques involved in the work were neither directly applicable nor extensible. In order to improve such problems, this paper was adopted the quadtree technique and proposed the algorithm for an optimal path planning autonomously in an environment and proved a validity through a simulation.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.120-126
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• 2010

This paper presents to study the path tracking method of AGV(autonomous guided vehicle) which has a laser guidance system. An existing automatic guided vehicles(AGVs) which were able to drive on wired line only had a automatic guidance system. However, the automatic guidance systems that those used had the high cost of installation and maintenance, and the difficulty of system change according to variation of working environment. To solve such problems, we make the laser guidance system which is consisted of a laser navigation and gyro, encoder. That is robust against noise, and flexible according to working environment through sensor fusion. The laser guidance system can do a perfect autonomous driving. However, the commercialization of perfect autonomous driving system is difficult, because the perfect autonomous driving system must recognize the whole environment of working space. Hence, this paper studied the path tracking of AGV using laser guidance system without wired line. The path tracking method is consisted of virtual path generation method and driving control method. To experiment, we use the fork-type AGV which is made by ourselves, and do a path tracking experiments repeatedly on same experimental environment. In result, we verified that proposed system is efficient and stable for actual fork-type AGV.