• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.2
• /
• pp.97-103
• /
• 2016

In this paper, a smartphone-controlled personal mobility system (PMS) with semi-autonomous navigation is developed. The proposed PMS moves to waypoints and then reaches the destination where the waypoints and destination are selected by the user using Google maps in a smartphone. The hardware environment consists of a GPS (Global Positioning System) in the smartphone and a compass sensor. In addtion, while it is moving in autonomous mode, the user can intervene and change the direction and speed of the PMS in order to avoid obstacles that may be encountered accidentally in a dynamic environment. That is why it is called "semi-autonomous navigation". Experimental results showed that the proposed PMS is effectively able to migrate to the waypoints and destination in both autonomous and manual modes.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.3
• /
• pp.251-257
• /
• 2012

Unmanned ground vehicles have important military, reconnaissance, and materials handling application. Many of these applications require the UGVs to move at high speeds through uneven, natural terrain with various compositions and physical parameters. This paper presents a framework for high speed autonomous navigation based on the integrated real time traversability. Specifically, the proposed system performs real-time dynamic simulation and calculate maximum traversing velocity guaranteeing safe motion over rough terrain. The architecture of autonomous navigation is firstly presented for high-speed autonomous navigation. Then, the integrated real time traversability, which is composed of initial velocity profiling step, dynamic analysis step, road classification step and stable velocity profiling step, is introduced. Experimental results are presented that demonstrate the method for a $6{\times}6$ autonomous vehicle moving on flat terrain with bump.

• Journal of the Korean Society of Systems Engineering
• /
• v.13 no.2
• /
• pp.18-25
• /
• 2017

The use of unmanned combat systems is of interest for future battlefield. Advanced techniques are being actively studied to build fully autonomous unmanned systems. However, there are technical, ethical and legal limitations for the fully autonomous unmanned combat systems. In addition, a remote controlled system is necessary so far in order to prepare for situations where fully autonomous unmanned systems fail to function properly. Thus, a procedure of developing operational requirements in system level is proposed and interface requirements of unmanned combat vehicles for remote control are described in this study.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.181-183
• /
• 1986

This paper describes the concept of ADS (Autonomous Decentralized System) and its application to FA (Factory Automation). The schemes of ADFAS (Autonomous Decentralized Factory Automation System) utilizing these concepts are presented.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.3
• /
• pp.217-223
• /
• 2015

Autonomous driving is no longer atechnology of the future since the development of autonomous vehicles has now been realized, and many technologies have already been developed for the convenience of drivers. For example, autonomous vehicles are one of the most important drive assistant systems. Among these many drive assistant systems, Cruise Control Systems are now a typical technology. This system constantly maintains a vehicle's speed and distance from a vehicle in front by using Radar or LiDAR sensors in real time. Cruise Control Systems do not only serve their original role, but also fulfill another role as a 'Driving Safety' measure as they can detect a situation that a driver did not predict and can intervene by assuming a vehicle's longitude control. However, these systems have the limitation of only focusing on driver safety. Therefore, in this paper, an Intelligent Cruise Control System that utilizes the path planning method and GIS is proposed to overcome some existing limitations.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.4
• /
• pp.509-523
• /
• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• Journal of the Korean Society of Systems Engineering
• /
• v.17 no.2
• /
• pp.129-138
• /
• 2021

Today, as the number of vehicles equipped with autonomous driving functions increases, the use of various sensors increases, and the complexity of system configuration increases. The ISO 26262 standard was published to prevent caused by systematic errors. Recently, the issue of external environmental factors rather than mechanical failure has increased. This issue is a problem outside of the scope of ISO 26262, and the ISO/DIS 21448 standard was published to solve this problem. Also, Mobileye proposed the RSS model that defined safe distance for dangerous situations in order to secure the safety of autonomous vehicles and who is responsible in case of an accident. In this paper, integrated process of ISO 21448 and RSS model, and through these results, we expect that possible to contribute to securing the safety and reliability of autonomous vehicles in the future.

• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.400-404
• /
• 1994

In this paper, we will investigate the position estimation problem for autonomous mobile robots. Formulating this as a state estimation problem for nonlinear SISO system, then we will apply several types of nonlinear observers. Simulation results of observer-based navigation control will be also provided.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.3
• /
• pp.343-348
• /
• 2007

Development of autonomous vehicle system that use magnetic position meter research of intelligence transportation system is progressed worldwide active by fast increase of vehicles. Among them, research about autonomous of vehicles occupies field. And autonomous of vehicles is element that path recognition is basic. Existent magnetic base autonomous system analyzes three-dimensional data of magnet marker to 3 axises magnetic sensor and recognized route. But because using Magnetic Wire and Magnetic Position Meter in treatise that see, measure side lateral error and propose system that driving. And system that compare with system of autonomous vehicles and propose wishes to verify by hardware of that specification and simple algorithm through an experiment that autonomous is available.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.3
• /
• pp.251-268
• /
• 2007

A Gaussian sum filter (GSF) is proposed in this paper on simultaneous localization and mapping (SLAM) for mobile robot navigation. In particular, the SLAM problem is tackled here for cases when only bearing measurements are available. Within the stochastic mapping framework using an extended Kalman filter (EKF), a Gaussian probability density function (pdf) is assumed to describe the range-and-bearing sensor noise. In the case of a bearing-only sensor, a sum of weighted Gaussians is used to represent the non-Gaussian robot-landmark range uncertainty, resulting in a bank of EKFs for estimation of the robot and landmark locations. In our approach, the Gaussian parameters are designed on the basis of minimizing the representation error. The computational complexity of the GSF is reduced by applying the sequential probability ratio test (SPRT) to remove under-performing EKFs. Extensive experimental results are included to demonstrate the effectiveness and efficiency of the proposed techniques.