http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Vehicle-to-Infrastructure (V2I) 정보 연동 실내 자율발렛주차 시스템
김민수(Minsoo Kim),안준우(Joonwoo Ahn),이양우(Yangwoo Lee),박재흥(Jaeheung Park) 한국자동차공학회 2022 한국자동차공학회 부문종합 학술대회 Vol.2022 No.6
In this paper, we propose the autonomous valet parking system with vehicle-to-infrastructure (V2I) communications for indoor parking. The proposed system utilizes V2I communications to obtain a navigation plan. It includes the vehicle’s position and information about which direction to head at each intersection. With only this navigation plan, the autonomous vehicle avoids obstacles and drives in response to an intersection. The experimental results showed that, with the proposed system, the vehicle achieves efficient and safe navigation and successfully parks at a real indoor parking environment.
안준우(Joonwoo Ahn),김민수(Minsoo Kim),임규범(GyuBeom Im),김민성(Minsung Kim),박재흥(Jaeheung Park) 한국자동차공학회 2018 한국자동차공학회 학술대회 및 전시회 Vol.2018 No.11
In this paper, we propose an efficient and safe method for autonomous valet parking system with a driving strategy considering uncertain environment in parking spaces. The proposed method consists of a vehicle controller with decision-making algorithms, a global and local path generation algorithm, and a three-dimensional LiDAR-based parking lot detection algorithm. The proposed method was validated via simulation results.
수직 주차에서 AVM을 이용한 동시적 위치추정 및 지도 생성
안찬우(Chanwoo Ahn),박재흥(Jaeheung Park) 한국자동차공학회 2020 한국자동차공학회 학술대회 및 전시회 Vol.2020 No.11
In this paper, we propose a Simultaeneous Localization And Mapping(SLAM) method for vertical parking scenario. Most commercial car uses ultrasonic sensor to localize vehicle’s position in parking lot. However, vehicle cannot be localized when there are not any obstacles around ego vehicle. The proposed method uses simple features from parking lines and localizes vehicle’s position without any assumption about obstacles around ego vehicle using only Around View Monitor(AVM). At first, cross point is proposed as a feature which can be used for tracking. Cross points on parking lines are detected using Deep Learning and parking lines are extracted using RANSAC and Canny Edge. Using detected cross points and parking lines, relative poses between frames are tracked using Iterative Closeset Point(ICP) and landmark based localization. Global position of detected cross point is used as landmark’s position and position of intersection from detected lines is used as local position of the corresponding cross point. Using landmark based localization, relative poses are calculated and accumulated errors are recovered. From above method, we build a 2D map which is continuously optimized. We evaluated our proposed approach on our own dataset and compared our result with LOAM(Lidar Odometry and Mapping in Real-time).
샘플링 기반 경로 계획과 모델 예측 제어를 이용한 자율 주차 시스템
김민성(Minsung Kim),박재흥(Jaeheung Park) 한국자동차공학회 2018 한국자동차공학회 부문종합 학술대회 Vol.2018 No.6
In this paper, we propose a path planning and a path following method for the autonomous parking system. In order to consider the non-holonomic constraint of a vehicle, RRT star is used to plan paths. Model predictive control with the vehicle kinematic model is proposed to follow the path. To realize the autonomous parking system, we also consider the path re-planning at the point where forward and reverse paths are switched. The proposed method was validated via simulation results.
주차환경에서 자율 주행 차량 실험을 위한 V-Rep 기반 시뮬레이터
임규범(GyuBeom Im),김민성(Minsung Kim),안준우(Joonwoo Ahn),김민수(Minsoo Kim),박재흥(Jaeheung Park) 한국자동차공학회 2018 한국자동차공학회 학술대회 및 전시회 Vol.2018 No.11
We propose a V-Rep vehicle simulator for autonomous vehicle testing in parking lot environment. When we validate a new algorithm or method in the real world, it could be dangerous and lead to safety accident or emergency situation. Therefore, it is beneficial to validate a new algorithm in a virtual simulator before doing in the real world. V-Rep simulator is a popularly used robot simulator. We can create our test environment and validate some algorithms using this simulator. And V-Rep is enable to interact with ROS (Robot Operating System) as a part of virtual parking lot environment. In this paper, we explain how to set up a parking lot environment and an autonomous vehicle model. And we explain how to validate planning, control algorithms using V-Rep and ROS.