Comparisonal Analysis of Path Planning Methods for Automatic Parking Control of a Car-Like Mobile Robot (original) (raw)

가중화된 GPS 정보와 지도정보를 활용한 실외 이동로봇의 위치추정

The Journal of Korea Robotics Society, 2011

Global positioning system (GPS) is widely used to measure the position of a vehicle. However, the accuracy of the GPS can be severely affected by surrounding environmental conditions. To deal with this problem, the GPS and odometry data can be combined using an extended Kalman filter. For stable navigation of an outdoor mobile robot using the GPS, this paper proposes two methods to evaluate the reliability of the GPS data. The first method is to calculate the standard deviation of the GPS data and reflect it to deal with the uncertainty of the GPS data. The second method is to match the GPS data to the traversability map which can be obtained by classifying outdoor terrain data. By matching of the GPS data with the traversability map, we can determine whether to use the GPS data or not. The experimental results show that the proposed methods can enhance the performance of the GPS-based outdoor localization.

Design of Lateral Fuzzy-PI Controller for Unmanned Quadrotor Robot

Journal of Institute of Control, Robotics and Systems, 2013

Quadrotor UAV (Unmanned Aerial Vehicle) is a flying robotic platform which has drawn lots of attention in the recent years. The attraction comes from the fact that it is able to perform agile VTOL (Vertical TakeOff Landing) and hovering functions. In addition, the efficient modular structure composed of four electric rotors makes its design easier compared to other single-rotor type helicopters. In many cases, a quadrotor often utilizes vision systems in order to obtain altitude control and navigation solution in hostile environments where GPS receivers are not working or deniable. For carrying out their successful missions, it is essential for flight control systems to have fast and stable control responses of heading angle outputs. This paper presents a Fuzzy Logic based lateral PI controller to stabilize and control the quadrotor vehicle equipped with vision systems. The advantage of using the fuzzy based PI controller lies in the fact that it could acquire a desired output response of a heading angle even in presence of disturbances and uncertainties. The performance comparison of the newly proposed Fuzzy-PI controller and the conventional PI controller was carried out with various simulation results.

Development of Jumping Mechanism for Small Reconnaissance Robot

2009

In the future, most military activities will be replaced by robots. Because of many dangerous factors in battlefield, reconnaissance should be performed by robot. Reconnaissance robot should be small for not being detected, be light and simple structure for personal portability and overcome unexpected rough terrain for mission completion. In case of small and light robot, it can't get enough friction force for movement. Therefore small reconnaissance robot need jumping function for movement. In this paper we proposed a biologically inspired jumping mechanism. And we adjusted moment and jumping angle by using four bar linkage, especially varying coupler length.

EEG Signal Classification Algorithm based on DWT and SVM for Driving Robot Control

Journal of the Institute of Electronics and Information Engineers, 2015

I n t h i sp a p e r ,wep r o p o s eac l a s s i f i c a t i o n a l g o r i t h m b a s e d o n t h eo b t a i n e d E E G(E l e c t r o e n c e p h a l o g r a m)s i g n a lf o rt h e c o n t r o lo f' l e f t 'a n d ' r i g h t 't u r n i n g so fwh i c h a d r i v i n g s y s t e m c o mp o s e d o fE E G s e n s o r ,L a b v i e w,DAQ,Ma t l a b a n d d r i v i n gr o b o t .Th ep r o p o s e da l g o r i t h m u s e sf e a t u r e se x t r a c t e df r o m f r e q u e n c yb a n di n f o r ma t i o no b t a i n e db yDWT(Di s c r e t e Wa v e l e tTr a n s f o r m)a n ds e l e c t sf e a t u r e so fh i g h d i s c r i mi n a t i o nb y u s i n g F i s h e rs c o r e .We ,a l s op r o p o s et h en u mb e ro f f e a t u r ev e c t o r sf o rt h eb e s tc l a s s i f i c a t i o n p e r f o r ma n c eb y u s i n g S VM(S u p p o r tVe c t o rMa c h i n e)c l a s s i f i e ra n d p r o p o s ea d e c i s i o np e n d i n g a l g o r i t h m b a s e do nML D(Ma x i mu m L i k e l i h o o dDe c i s i o n)t op r e v e n tma l f u n c t i o nd u et omi s c l a s s i f i c a t i o n. Th es e l e c t e df o u rf e a t u r ev e c t o r sf o rt h ep r o p o s e da l g o r i t h m a r et h eme a no fa b s o l u t ev a l u eo fv o l t a g ea n dt h es t a n d a r d d e v i a t i o no fd 5 (2-4 Hz)a n dd 2 (1 6-3 2 Hz)f r e q u e n c yb a n d so fP 8c h a n n e la c c o r d i n g t ot h ei n t e r n a t i o n a ls t a n d a r de l e c t r o d e p l a c e me n tme t h o d .B y u s i n g t h e S VM c l a s s i f i e r ,we o b t a i n e d 9 8. 7 5 % a c c u r a c y a n d 1. 2 5 % e r r o rr a t e .Al s o ,wh e n we s p e c i f y e r r o rp r o b a b i l i t y o f7 0 % f o rd e c i s i o n p e n d i n g ,we o b t a i n e d 9 5. 6 3 % a c c u r a c y a n d 0 % e r r o rr a t e b y u s i n g t h e p r o p o s e dd e c i s i o np e n d i n ga l g o r i t h m.

A Real-time and Off-line Localization Algorithm for an Inpipe Robot by Detecting Elbows

제어로봇시스템학회 논문지, 2014

Robots used for pipe inspection have been studied for a long time and many mobile mechanisms have been proposed to achieve inspection tasks within pipelines. Localization is an important factor for an inpipe robot to perform successful autonomous operation. However, sensors such as GPS and beacons cannot be used because of the unique characteristics of inpipe conditions. In this paper, an inpipe localization algorithm based on elbow detection is presented. By processing the projected marker images of laser pointers and the attitude and heading data from an IMU, the odometer module of the robot determines whether the robot is within a straight pipe or an elbow and minimizes the integration error in the orientation. In addition, an off-line positioning algorithm has been performed with forward and backward estimation and Procrustes analysis. The experimental environment has consisted of several straight pipes and elbows, and a map of the pipeline has been constructed as the result.

Design and Implementation of Real-Time Vehicle Safety System based on Wireless Sensor Networks

The Journal of the Institute of Webcasting, Internet and Telecommunication, 2008

Wireless sensor networks achieve environment monitoring and controlling through use of small devices of low cost and low power. Such network is comprised of several sensor nodes, each having a microprocessor, sensor, actuator and wired/wireless transceiver inside a small device. In this paper, we employ the sensor networks in order to design and implement a real-time vehicle safety system. Such system can inform the safe velocity in a specific weather condition to drivers in advance through analyzing the weather data collected from sensor networks. As a result, the drivers can prevent effectively accidents by controlling their car speed.

Classification of 3D Road Objects Using Machine Learning

Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 2018

Autonomous driving can be limited by only using sensors if the sensor is blocked by sudden changes in surrounding environments or large features such as heavy vehicles. In order to overcome the limitations, the precise road-map has been used additionally. This study was conducted to segment and classify road objects using 3D point cloud data acquired by terrestrial mobile mapping system provided by National Geographic Information Institute. For this study, the original 3D point cloud data were pre-processed and a filtering technique was selected to separate the ground and non-ground points. In addition, the road objects corresponding to the lanes, the street lights, the safety fences were initially segmented, and then the objects were classified using the support vector machine which is a kind of machine learning. For the training data for supervised classification, only the geometric elements and the height information using the eigenvalues extracted from the road objects were used. The overall accuracy of the classification results was 87% and the kappa coefficient was 0.795. It is expected that classification accuracy will be increased if various classification items are added not only geometric elements for classifying road objects in the future.

Matlab Gui 기반 GPS Rinex 관측 파일 생성 소프트웨어의 개발

The Journal of Korea Navigation Institute, 2015

This paper introduces development of the MATLAB GUI based software for generating GPS RINEX observation file. The purpose of this software is to generate GPS measurements of reference station or dynamic user, which are similar to the real GPS receiver data, accurately and efficiently. This software includes two data generation modes. One is Precision mode which generates GPS measurements as accurate as possible using post-processing data. The other is Real-time mode which generates GPS measurements using GPS error modeling technique. GPS error sources are calculated on the basis of each data generation mode, and L1/L2 pseudorange, L1/L2 carrier phase, and Doppler measurements are produced. These generated GPS measurements are recorded in the RINEX observation version 3.0 file. Using received GPS data at real reference station, we analyzed three items to verify software reliability; measurement bias, rate of change, and noise level. Consequently, RMS error of measurement bias is about 0.7 m, and this verification results demonstrate that our software can generate relatively exact GPS measurements.