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An Intelligent Auto Parking System for Vehicles
Anastasia Razinkova1,조현찬,전홍태 한국지능시스템학회 2012 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.12 No.3
Autoparking assistant systems are a new and very promising area in automotive systems engineering. Since the traffic in modern cities becomes more intense, it is getting harder for a driver. Those systems are necessary for an inexperienced one to find a proper parking slot, or to park in a narrow parking slot without damaging his car or the vehicles around. The implementation of autoparking assistant systems may reduce drivers’ stress and make parking generally more comfortable. In addition, such system can be extremely useful for senior or disabled people or for drivers with reduced mobility. The implementation of autoparking assistant systems may increase the safety of the parking, and therefore the development of such systems is a highly-demanded task. We introduce an intelligent autoparking system that automatically generates trajectory for parking using a fuzzy logic. This paper consists of three parts. In first part we introduce trajectory generation method for parallel parking without collisions. Fuzzy-logic based trajectory generation algorithm is described in second part. Experimental results presented in the third part of the paper prove effectiveness of the proposed method.
Constant Altitude Flight Control for Quadrotor UAVs with Dynamic Feedforward Compensation
Anastasia Razinkova1,강병준,조현찬,전홍태 한국지능시스템학회 2014 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.14 No.1
This study addresses the control problem of an unmanned aerial vehicle (UAV) during thetransition period when the flying mode changes from hovering to translational motion inthe horizontal plane. First, we introduce a compensation algorithm that improves heightstabilization and reduces altitude drop. The main principle is to incorporate pitch and rollmeasurements into the feedforward term of the altitude controller to provide a larger thrustforce. To further improve altitude control, we propose the fuzzy logic controller that improvessystem behavior. Simulation results presented in the paper highlight the effectiveness of theproposed controllers.
Intelligent Path Generation for Parking Assistant System
Anastasia Razinkova(아나스타샤 Razinkova),Hyun-Chan Cho(조현찬),Hong-Tae Jeon(전홍태) 대한전자공학회 2010 대한전자공학회 학술대회 Vol.2010 No.6
This paper considers the problem of parallel parking for vehicles. An intelligent method for real-time path generation is presented. This study addresses general cases of parallel parking within a rectangular space. Generated path consists of maneuvers with different curvature. Thus, a fuzzy system is used to select the most suitable maneuver from the solution set according to the environment, dealing with optimality, path tracking performance and collision avoidance trade-off. The simulation results presented in this paper show that proposed system has good performance with different environment parameters. This strategy is developed to help human drivers and will be implemented in a real vehicle in future.
An Intelligent Auto Parking System for Vehicles
Razinkova, Anastasia,Cho, Hyun-Chan,Jeon, Hong-Tae Korean Institute of Intelligent Systems 2012 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.12 No.3
Autoparking assistant systems are a new and very promising area in automotive systems engineering. Since the traffic in modern cities becomes more intense, it is getting harder for a driver. Those systems are necessary for an inexperienced one to find a proper parking slot, or to park in a narrow parking slot without damaging his car or the vehicles around. The implementation of autoparking assistant systems may reduce drivers' stress and make parking generally more comfortable. In addition, such system can be extremely useful for senior or disabled people or for drivers with reduced mobility. The implementation of autoparking assistant systems may increase the safety of the parking, and therefore the development of such systems is a highly-demanded task. We introduce an intelligent autoparking system that automatically generates trajectory for parking using a fuzzy logic. This paper consists of three parts. In first part we introduce trajectory generation method for parallel parking without collisions. Fuzzy-logic based trajectory generation algorithm is described in second part. Experimental results presented in the third part of the paper prove effectiveness of the proposed method.
Constant Altitude Flight Control for Quadrotor UAVs with Dynamic Feedforward Compensation
Razinkova, Anastasia,Kang, Byung-Jun,Cho, Hyun-Chan,Jeon, Hong-Tae Korean Institute of Intelligent Systems 2014 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.14 No.1
This study addresses the control problem of an unmanned aerial vehicle (UAV) during the transition period when the flying mode changes from hovering to translational motion in the horizontal plane. First, we introduce a compensation algorithm that improves height stabilization and reduces altitude drop. The main principle is to incorporate pitch and roll measurements into the feedforward term of the altitude controller to provide a larger thrust force. To further improve altitude control, we propose the fuzzy logic controller that improves system behavior. Simulation results presented in the paper highlight the effectiveness of the proposed controllers.
Adaptive Control over Quadcopter UAV under Disturbances
Anastasia Razinkova,Igor Gaponov,Hyun-Chan Cho 제어로봇시스템학회 2014 제어로봇시스템학회 국제학술대회 논문집 Vol.2014 No.10
This paper is concerned with adaptive compensation for position tracking error of quadrotor UAVs. We propose an adaptive compensation scheme which effectively reduces errors in tracking desired position along X- and Y-axis in the presence of constant disturbance. The proposed control strategy is verified through extensive computer simulations. Implementation of the designed adaptive compensator allowed to reduce tracking error by a factor of 3 and can be effectively used in practical quadcopters.
An Intelligent Auto Parking System for Vehicles
Anastasia Razinkova,Hyun-Chan Cho,Hong-Tae Jeon 한국지능시스템학회 2012 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.12 No.3
Autoparking assistant systems are a new and very promising area in automotive systems engineering. Since the traffic in modern cities becomes more intense, it is getting harder for a driver. Those systems are necessary for an inexperienced one to find a proper parking slot, or to park in a narrow parking slot without damaging his car or the vehicles around. The implementation of autoparking assistant systems may reduce drivers’ stress and make parking generally more comfortable. In addition, such system can be extremely useful for senior or disabled people or for drivers with reduced mobility. The implementation of autoparking assistant systems may increase the safety of the parking, and therefore the development of such systems is a highly-demanded task. We introduce an intelligent autoparking system that automatically generates trajectory for parking using a fuzzy logic. This paper consists of three parts. In first part we introduce trajectory generation method for parallel parking without collisions. Fuzzy-logic based trajectory generation algorithm is described in second part. Experimental results presented in the third part of the paper prove effectiveness of the proposed method.
Constant Altitude Flight Control for Quadrotor UAVs with Dynamic Feedforward Compensation
Anastasia Razinkova,Byung-Jun Kang,Hyun-Chan Cho,Hong-Tae Jeon 한국지능시스템학회 2014 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.14 No.1
This study addresses the control problem of an unmanned aerial vehicle (UAV) during the transition period when the flying mode changes from hovering to translational motion in the horizontal plane. First, we introduce a compensation algorithm that improves height stabilization and reduces altitude drop. The main principle is to incorporate pitch and roll measurements into the feedforward term of the altitude controller to provide a larger thrust force. To further improve altitude control, we propose the fuzzy logic controller that improves system behavior. Simulation results presented in the paper highlight the effectiveness of the proposed controllers.
A Trajectory Generation Algorithm in Autonomous Parking System using Fuzzy Logic Control
아나스타샤(Anastasia Razinkova),조현찬(Hyun-Chan Cho) 한국지능시스템학회 2009 한국지능시스템학회 학술발표 논문집 Vol.19 No.2
This paper considers the problem of parallel parking for vehicles. A semi-autonomous parking system and a method for real-time trajectory planning are presented. This study addresses general cases of parallel parking within a rectangular space. Generated trajectory consists of maneuvers with different curvature. Thus, a fuzzy system is used to select the most suitable maneuver from the solution set according to the environment, dealing with optimality, path tracking performance and collision avoidance trade-off. This technique has been implemented in a fuzzy behavior-based control architecture combining planning and reactivity. This strategy is developed to help human drivers and will be implemented in a real vehicle in future.