• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1051-1058
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• 2011

Unmanned autonomous forklifts have a great potential to enhance the productivity of material handling in various applications because these forklifts can pick up and deliver loads without an operator and any fixed guide. Especially, automation of pallet loading and unloading technique is useful for enhancing performance of logistics and reducing cost for automation system. There are, however, many technical difficulties in developing such forklifts including localization, map building, sensor fusion, control, and so on. This is because the system requires numerous sensors, actuators, and controllers that need to be connected with each other, and the number of connections grows very rapidly as the number of devices grows. This paper presents a vision sensorbased autonomous loading and unloading for network-based unmanned forklift where system components are connected to a shared CAN network. Functions such as image processing and control algorithm are divided into small tasks that are distributed over a number of microcontrollers with a limited computing capacity. And the experimental results show that proposed architecture can be an appropriate choice for autonomous loading in the unmanned forklift.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.129-143
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• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.138.5-138
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• 2001

The autonomous robot has the ability of obstacle avoidance and target tracking with some manufactured information. In this paper, it is shown that autonomous mobile robot can avoid fixed obstacles using the map made before and the fuzzy controller is adopted with the global path planing and the local path planing when the robot navigates. With that map sensor, information will be used when an autonomous robot navigates. This paper proves that robot can navigate through optimized route and keep the stable condition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.323-326
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• 1995

During a fast decade, an automatic control technology makes an aggressive improvement with the developments of computer and communication technology. In large scale and complicated systems, an autonomous decentralized control system is required in which the sub-systems must have some ability such that the self-judgement and self-performance functions. In this paper, we propose an algorithm to realized these functions using micro mobile robot which is applied to a control of a werehouse. The proposed algorithm is based on performance index, and the selecting rules of the task between the sub-systems are induced by the index. Also, it is effected by weighting function which is determined by environment and kind of works. To verify the effectiveness of this algorithm, we develop the simulator to implement the autonomous decentralized control and apply to the micro mobile robot on the PC machine.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.528-533
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• 2004

The purpose of this thesis is to construct the autonomous decentralized train traffic management structure using techniques of Autonomous Decentralized System. Currently, a method of train traffic control is making use of CTC(Centralized Traffic Control). Its operation method is divided into the remote mode and the local mode. The classified basis is according to the control authority of install signals in track side. In most cases, a large scale station is operated by the local mode. Because of dispatchers in center can not control the shunting works influence on the main route. In order to solve these problem s, we analyzed a current operation condition and system requirements. Moreover, this thesis is constructing autonomous decentralized train traffic management structure. Finally, this research proposed that interface with CTC and step-by-step construction.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.4
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• pp.244-250
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• 2008

This paper describes the design and implementation of an unmanned ground vehicle (UGV) and also estimates how well autonomous navigation and remote control of UGV can be performed through the optimized arbitration of several sensor data, which are acquired from vision, obstacle detection, positioning system, etc. For the autonomous navigation, lane detection and tracing, global positioning, and obstacle avoidance are necessarily required. In addition, for the remote control, two types of experimental environments are established. One is to use a commercial racing wheel module, and the other is to use a haptic device that is useful for a user application based on virtual reality. Experimental results show that autonomous navigation and remote control of the designed UGV can be achieved with more effectiveness and accuracy using the proper arbitration of sensor data and navigation plan.

• Agricultural and Biosystems Engineering
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• v.2 no.2
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• pp.50-58
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• 2001

Chemical application is very hazardous in confined spaces under the canopy ceiling in Korean vineyard. For a small orchard sprayer adaptable to such a working condition, a low-cost autonomous steering control system was developed using two ultrasonic sensors, two electrically-operated cylinders and 80196kc microprocessor. A distance ranging system timed the round-trip for each ultrasonic wave to travel against parallel targets, placed every 1.5m spacing along both sides of a desired path. A steering control algorithm of the autonomous operation began with ranging left and right targets and the heading was decided using difference between the distances. Electrically-operated cylinders actuated steering clutches to guide the sprayer. Evaluation tests showed that the orchard sprayer could travel within RMS value of 5cm along the desired path. Ground speed did not affect the performance of the autonomous guidance system at the speed ranges of 0.29~0.52m/sec.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.617-624
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• 2010

This article describes the system architecture of KUVE (KIST Unmanned Vehicle Electric) and unmanned autonomous navigation of it in KIST. KUVE, which is an electric light-duty vehicle, is equipped with two laser range finders, a vision camera, a differential GPS system, an inertial measurement unit, odometers, and control computers for autonomous navigation. KUVE estimates and tracks the boundary of road such as curb and line using a laser range finder and a vision camera. It follows predetermined trajectory if there is no detectable boundary of road using the DGPS, IMU, and odometers. KUVE has over 80% of success rate of autonomous navigation in KIST.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.451-459
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• 2011

Fundamentally, there are 5 systems are needed for autonomous navigation of unmanned ground vehicle: Localization, environment perception, path planning, motion planning and vehicle control. Path planning and motion planning are accomplished based on result of the environment perception process. Thus, high reliability of localization and the environment perception will be a criterion that makes a judgment overall autonomous navigation. In this paper, via map matching using vehicle dynamic model and LIDAR sensors, replace high price localization system to new one, and have researched an algorithm that lead to robust autonomous navigation. Finally, all results are verified via actual unmanned ground vehicle tests.

• Journal of Power Electronics
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• v.15 no.4
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• pp.1054-1065
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• 2015

Multi-functional voltage source inverters (VSIs) have attracted increasing attention in recent years for their advantageous auxiliary services for power quality enhancement in autonomous microgrids. These types of VSIs can not only achieve a proper control scheme in autonomous mode but also cope with the prescribed power quality and stability requirements. These functionalities are integrated within the same device, thereby significantly improving the cost-effectiveness of microgrids while decreasing the investment and bulk compared with those of multiple devices with independent functionalities. Control strategies for power quality enhancement in autonomous microgrids using multi-functional VSIs are comprehensively reviewed in this paper. In addition, such VSIs are discussed in detail, and comparisons of which are also provided. Lastly, a number of future research directions for multi-functional VSIs are recommended.