• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.7
• /
• pp.599-605
• /
• 2017

For an unmanned vehicle to be driven on the off-road terrain, it is necessary to consider the vehicle's stability. This paper suggests a path tracking controller for simulation of real-time vehicle stability analysis. The path tracking controller uses the preview distance to track the given trajectory. The disturbance moment is estimated using the yaw moment observer, and this information is used for compensation in the yaw moment control. On a curved path, the vehicle's desired velocity is determined from the curvature of the path. Because the vehicle is equipped with six independent motor driven wheels, the driving torques are distributed on all the wheels. The effectiveness of the path tracking controller is verified using ADAMS/MATLAB co-simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.22 no.11
• /
• pp.1054-1062
• /
• 2011

This study describes the time domain imaging algorithm which can be well applied to short-range UWB(ultra wideband) bistatic radar. In the imaging method of SAR technology, the frequency domain method is well applied to the areas which satisfy far-field condition. However in the near-field environment, the image quality is not good due to phase error. However back-projection method based on time domain is well applied to short-range imaging radar. Meanwhile because its processing time is very long, real time-processing is very difficult. To resolve this problem FFBP(Fast Factorized Back-Projection) was proposed. Using the raw data gathered on field we implemented back-projection and FFBP method. Then image quality and processing time were analyzed using these methods.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.4 no.2
• /
• pp.69-78
• /
• 2009

Localization is a very important technique for the mobile robot to navigate in outdoor environment. In this paper, the development of the sensor fusion algorithm for controlling mobile robots in outdoor environments is presented. The multi-sensorial dead-reckoning subsystem is established based on the optimal filtering by first fusing a heading angle reading data from a magnetic compass, a rate-gyro, and two encoders mounted on the robot wheels, thereby computing the dead-reckoned location. These data and the position data provided by a global sensing system are fused together by means of an extended Kalman filter. The proposed algorithm is proved by simulation studies of controlling a mobile robot controlled by a backstepping controller and a cascaded controller. Performances of each controller are compared.

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

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.1
• /
• pp.25-30
• /
• 2013

In military vehicles moving over poor roads, severe vibration of the chassis can damage internal components. Currently, many studies have focused on active and semi-active suspensions to reduce the vibration of the chassis. In this study, a vibration reduction technique is suggested by applying a unique rotating suspension structure. SH-ADD, a type of modified Skyhook, was selected as a controller for vibration reduction. A random ISO class E road was selected as the driving road. The simulation was performed using ADAMS Control and Matlab Simulink. The control result was compared with the RMS acceleration with a focus on the cumulative fatigue of the internal equipment.

• Journal of Korean Society for Geospatial Information Science
• /
• v.22 no.3
• /
• pp.79-85
• /
• 2014

For the successful operation of unmanned ground vehicles(UGVs), optimal path planning should be considered with trafficability analysis, threat analysis, and so on. From among these, trafficability analysis is immensely important for safeness of UGVs especially in the case of driving the off-road such as unpaved road, grassland, and open fields. Geographical information has a pivotal role in extracting data and measuring cost for specified regions of interest. In this paper, we review possibilities to apply Land Cover Map(LCM) as a new, fundamental source and propose a new generation method of trafficability analysis map for optimal path planning of UGV. The simulation results show that the proposed method significantly improve the previous method by applying LCM either alone or in combination with the other GIS.

• The Journal of Korea Robotics Society
• /
• v.13 no.3
• /
• pp.174-181
• /
• 2018

For a mobile robot that travels along a terrain consisting of various geology, information on tire force and friction coefficient between ground and wheel is an important factor. In order to estimate the lateral force between ground and wheel, a lot of information about the model and the surrounding environment of the vehicle is required in conventional method. Therefore, in this paper, we are going to estimate lateral force through simple model (Minimal Argument Lateral Slip Curve, MALSC) using only minimum data with high estimation accuracy and to improve estimation reliability of the friction coefficient by using the estimated lateral force data. Simulation is carried out to analyze the correlation between the longitudinal and transverse friction coefficients and slip angles to design the simplified lateral force estimation model by analysing simulation data and to apply it to the actual field environment. In order to verify the validity of the equation, estimation results are compared with the conventional method through simulation. Also, the results of the lateral force and friction coefficient estimation are compared from both the conventional method and the proposed model through the actual robot running experiments.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.6
• /
• pp.55-59
• /
• 2008

For effective mobility control of UGV(unmanned ground vehicle), the terrain cover classification is an important component as well as terrain geometry recognition and obstacle detection. The vision based terrain cover classification algorithm consists of pre-processing, feature extraction, classification and post-processing. In this paper, we present a method to classify terrain covers based on the color and texture information. The color space conversion is performed for the pre-processing, the wavelet transform is applied for feature extraction, and the SVM(support vector machine) is applied for the classifier. Experimental results show that the proposed algorithm has a promising classification performance.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.9
• /
• pp.883-895
• /
• 2007

In this work, we present the development of a patrol robot which is intended to navigate outdoor rough terrain. Proposed mechanism consists of six legs for overcoming an obstacle, and six wheels for traveling. Also, in order to absorb vibration in rough terrain effectively, the slide-spring system and tubed type tire are adopted to each leg and each wheel. The control system of robot consists of several imbedded boards for management of lots of diverse devices such as sensors designed for rough terrain, motor controllers, camera, micro controller and so on. And the base system of the robot is designed to operate in real time and to surveille in the vicinity of the robot, and the robot system is controlled by wireless LAN connected to GUI-based remote control system, while CAN communication connects the control board and the device controllers for sensors and motor controllers. For operating this robot system efficiently, we propose the control algorithms for autonomous navigation using GPS, stabilization maintenance by posture control, obstacle-avoidance by impedance control, and obstacle-overcoming with interference-avoidance between wheels. The performance of the robot and the proposed algorithms are tested and proved by a set of experiments in outdoor rough terrain.

• The Journal of Korea Robotics Society
• /
• v.9 no.2
• /
• pp.124-131
• /
• 2014

The robot mechanisms that were previously researched had only been conducted for the purpose of overcoming the obstacles stably at low speed driving and enhancing the stability against high speed circuitous driving, and yet, the mechanism satisfying two purposes. However, in order to stably drive with high speed on rough terrain, there is a need for satisfying both of these purposes, as well as testing the efficiency of the mechanisms at high speed driving. There, this paper simulated some of the passive mechanisms and focused on checking the performances of passive mechanisms through simulations and analyzing each mechanism on the basis of an evaluation index. The simulation was conducted by Adams (The Multi-body Dynamics Simulation Solution) and used various types of passive mechanisms which were introduced in the robotics field. As a result, the study confirmed that passive mechanisms have a number of situations that affect the driving stability on each direction of roll and pitch. Further study is needed about active mechanism.