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이한섭
Приєднався 28 сер 2012
Generation Obstacle Area using RVIZ
This video shows the generation of obstacle areas in an urban environment.
There is a mouse event function in RVIZ, so the clicked point is visualized by MarkerArray.
We can use this application for such as global path planning.
There is a mouse event function in RVIZ, so the clicked point is visualized by MarkerArray.
We can use this application for such as global path planning.
Переглядів: 101
Відео
UAM simulation environment designed for ETRI
Переглядів 1658 місяців тому
This video is about the simulation environment designed for ETRI, demonstrating a scenario of UAM (Urban Air Mobility) operation. The simulation was developed using GAZEBO, incorporating terrain with elevation data. The buildings on the map were created using Blender. Through this simulation, we aim to verify UAM operations, including waypoint following, handling emergency situations, and testi...
GAZEBO Elevator Model Custom Plugin for Control
Переглядів 180Рік тому
This video introduces a custom GAZEBO plugin designed specifically for controlling the elevator model. Our research focuses on Last-Mile Delivery utilizing robots and drones. In order to successfully deliver goods, the delivery robot needs to navigate within buildings. We required a custom control solution to verify our integrated system's functionality. Typically, I create GAZEBO models using ...
3D Path Planning Test in 2020 AI Grand Challenge Map
Переглядів 216Рік тому
This is a test video about 3D path planning in 2020 AI Grand Challenge map. At the competition, we used 2D path planning with the additional guidance for the vertical obstacles. We were the first prize while we had completed all the courses with 2D planner. In this case, we apply the 3D path planning method and overcome the all obstacles. I just test to pass a few obstacles with 'EGO-Planner' (...
편미분방정식 - Cauchy Riemann 방정식
Переглядів 55Рік тому
복소함수의 미분에서 나오는 Cauchy Riemman Equation과 조화함수(Harmonic Function)에 대한 내용 정리입니다.
편미분방정식 - 파동방정식
Переглядів 59Рік тому
편미분방정식 강의에서 경계값 문제에서 1차 파동함수의 증명 및 솔루션 정리 입니다. 필기노트 풀버전 researchnote.tistory.com/15
편미분방정식 - Fourier Series
Переглядів 28Рік тому
편미분방정식에서 Fourier Series 내용 정리입니다. 필기노트 풀버전 researchnote.tistory.com/14
강화학습 - Actor/Critic 알고리즘
Переглядів 69Рік тому
강화학습 기법 중 Actor-Critic에 대한 정리입니다. 필기노트 풀버전 researchnote.tistory.com/13
선형시스템제어 - transient response
Переглядів 30Рік тому
1st order system 과 2nd order system의 transient response 정리 입니다.
선형시스템제어 - transfer function
Переглядів 41Рік тому
Dynamic System을 분석하기 위한 Laplace Transform과 Transfer Function에 대한 정리입니다.
선형시스템제어 - controllability
Переглядів 84Рік тому
선형시스템제어 controllability 정의 및 증명 필기노트 풀버전 researchnote.tistory.com/17
강화학습 - Policy Gradient
Переглядів 53Рік тому
U.C. Berkeley Sergey Levine 교수님의 강화학습 강의 필기노트 입니다. Policy Gradient 방법의 유도 과정과 Reducing Variance에 대한 내용입니다. 필기노트 풀버전 researchnote.tistory.com/10
Demonstration of drone delivery from the ground to the rooftop
Переглядів 158Рік тому
This video is about the demonstration of drone delivery. Our goal is to load packages from the ground and deliver them to the rooftop. The drone has the capability of a 3kg payload and 20 minutes of operation time. In this scenario, the tracking speed is 3m/s, and the drone performs the vision-based landing when it approaches the marker. We implement the Mobilenet SSD to detect the H-marker, an...
RH-RRT based Collision-free Landing Path Planning
Переглядів 3062 роки тому
This video shows that the landing path planning with obstacle avoidance using RH-RRT* algorithm. First, it finds the optimal landing path to approach the vertical way. Then the drone follows the landing path using the real-time sample-based path planning, RH-RRT* In this study, we develop the RH-RRT* in 3-dimensional space in real-time generating the 3D biased random sample and removing the nod...
Collision-free Vertical Landing Angle Control Guidance
Переглядів 702 роки тому
Collision-free Vertical Landing Angle Control Guidance
Landing Angle Control (LAC) simulation
Переглядів 702 роки тому
Landing Angle Control (LAC) simulation
Vision-based Autonomous Landing Simulation Test (for Delivery Drone)
Переглядів 922 роки тому
Vision-based Autonomous Landing Simulation Test (for Delivery Drone)
Indoor navigation flight test using FAST-LIO with Ouster LiDAR (OS0-32)
Переглядів 3942 роки тому
Indoor navigation flight test using FAST-LIO with Ouster LiDAR (OS0-32)
Receding Horizon based RRT* Real-time Path Planning 3D version Flight Test
Переглядів 1,8 тис.2 роки тому
Receding Horizon based RRT* Real-time Path Planning 3D version Flight Test
2020 MBZIRC Mission1 Task1 Piercing the Balloons Trial Day
Переглядів 432 роки тому
2020 MBZIRC Mission1 Task1 Piercing the Balloons Trial Day
Deep Learning based Drone Tracking by an Autonomous UAV using a Monocular Camera
Переглядів 792 роки тому
Deep Learning based Drone Tracking by an Autonomous UAV using a Monocular Camera
2019.10. Anti Drone Flight Test - Net Catching (안티드론 포획 검증 비행테스트)
Переглядів 512 роки тому
2019.10. Anti Drone Flight Test - Net Catching (안티드론 포획 검증 비행테스트)
2019.10. Anti Drone Flight Test - Tracking (안티드론 추적 검증 비행테스트)
Переглядів 602 роки тому
2019.10. Anti Drone Flight Test - Tracking (안티드론 추적 검증 비행테스트)
2020 MBZIRC Mission1 Task2 Flight Test - Grasping the Red Ball (2020 MBZIRC 미션1 비행실험)
Переглядів 172 роки тому
2020 MBZIRC Mission1 Task2 Flight Test - Grasping the Red Ball (2020 MBZIRC 미션1 비행실험)
2020 MBZIRC Mission1-1 Flight Test #2 - Piercing Static Balloon (2020 MBZIRC 미션1 비행실험)
Переглядів 142 роки тому
2020 MBZIRC Mission1-1 Flight Test #2 - Piercing Static Balloon (2020 MBZIRC 미션1 비행실험)
2020 AI Grand Challenge GAZEBO Simulation Result Video (2020 인공지능 그랜드 챌린지 시뮬레이션 결과 영상)
Переглядів 992 роки тому
2020 AI Grand Challenge GAZEBO Simulation Result Video (2020 인공지능 그랜드 챌린지 시뮬레이션 결과 영상)
2019 AI Grand Challenge - Half Sized Arena Best Record (2019 인공지능 그랜드 챌린지 비행 실험)
Переглядів 222 роки тому
2019 AI Grand Challenge - Half Sized Arena Best Record (2019 인공지능 그랜드 챌린지 비행 실험)
Landing Test Video (Static & Dynamic Marker and Moving Vehicle) 무인기를 이용한 착륙실험(정적 마커, 동적 마커, 움직이는 트럭)
Переглядів 252 роки тому
Landing Test Video (Static & Dynamic Marker and Moving Vehicle) 무인기를 이용한 착륙실험(정적 마커, 동적 마커, 움직이는 트럭)
hi,it's wonderful. I am very interested in your project and I want to know how to navigate using Octomap. It is possible to provide the github about this project? thx!
"promosm"
이렇게 승차감이 좋아보이는 엘리베이터는 처음이네요..
아직 마지막쯤에 늦어지는게 있어서 게인튜닝 더 해야돼ㅋㅋㅋ
우와! ! Gazebo 커뮤니티에 올리면 엄청 좋아할 것 같은데요??
에이ㅋㅋ 그정도는 아냐ㅋㅋ 그리고 커뮤니티 사람들 정도면 URDF로 원하는거 다 만들겠지ㅋㅋㅋㅋ
ㅎㅎ 이박사님 못하는게 없구먼요!
아고 교수님 별말씀을ㅎㅎㅎ 온 세상을 모델링하는 그날까지 해보겠습니다ㅋㅋ
hello, can you share the codes please?
이박사 대단대단~~!
석사 1년차에 들었던걸 이제 정리하네요ㅋㅋㅋㅋ
안녕하세요, 이한섭 박사님! 지난 여름에 ETRI에서 연구연수생으로 활동했던 대학생입니다. 박사님께서 제작하신 영상이 유튜브 알고리즘에 떠서 반갑네요 ㅎㅎㅎㅎ
안녕하세요! 이 대학생의 친구입니다. 드론에 관심이 있어서 따라 왔어요!
제가 그때 너무 바빠서 많이 못 챙겨드렸던 것 같은데 ETRI에서 좋은 성취 있으셨길 바라겠습니다!^^
Could you plz share the demo's repository?
Sorry, this project is just a test using open source from SLAM, PX4, etc. If you need any help, let me know specifically through lee2000zxc@gmail.com. Thank you for your interest :)
Hello I'm so interested in what you do.Can I ask you a few questions.I hvae sent you an mail in my email .I hope you can see.
Cool. Do you use Ouster python SDK?
No, I just modified velodyne plugin to fit the ouster spec. Thanks for interest :)
sir ı have no money but need acces to your papers please help me out
Please help me Sir ı am really intreasted in UAV based AI and dont know where to start
sir ı am really a fan your work and despertly need help for my project which is about Autonomous Dogfihting UAV and ı dont really have a lot information about how am ı going to follow The enemy UAV from camera input. How can ı get contact with you ?
You can contact me through E-mail. It is lee2000zxc@gmail.com. If you have any question, let me know.
Sir, ı am really a fan your work and despertly need help for my project which is about Autonomous Dogfihting UAV and ı dont really have a lot information about how am ı going to follow The enemy UAV from camera input. How can ı get contact with you ?
First of all, thank you for your interest. You can find the paper below. arc.aiaa.org/doi/abs/10.2514/6.2018-1593. This article is the previous work. Just replace the detection part with a deep learning algorithm. The GNC structure is almost identical.
@@user-zy5hf2sf1z Thanks a lot but any chance that ı can get acces to source code or may be a scratch :)
nice flight, what do you think our videos
really cool ;)
Is there any source or documentary that i can read? Thanks btw, your project is so cool
Thanks! You can reach the paper hear, arc.aiaa.org/doi/10.2514/6.2017-0676. Actually, It's not the recent paper. I'm writing a new version. Coming soon!
@@user-zy5hf2sf1z Is new paper out and are you open to collaborate. I am working on a similar project.
이박사님은 데이터링크 뭐써요 ? wifi? 433? 915?
주로 wifi를 씁니다ㅋㅋ 출력별로 다양하게 있어서 실내/실외 전부 wifi 사용하고 있습니다ㅋㅋ
@@user-zy5hf2sf1z 오 ~ 아주 잘 되네요 . ㅎㅎ
@@gunheemoon6279 간단한거라 다음엔 더 복잡한걸로 테스트 해볼게요ㅋㅋㅋㅋ
Cool! I see a few twitches in the position control. Where is this coming from?
I guess, the drone model is not proper using default velocity control gain and attitude control gain. I didn't try hard gain tuning in GAZEBO environment :)
@@user-zy5hf2sf1z Ah, okay cool. I think its not the attitude / velocity gain but coming from the setpoints. but anyway cool project! FYI, it is much easier to have complex scenes now in PX4 SITl gazebo such as : ua-cam.com/video/ir1fwOLcd4E/v-deo.html
@@jaeyounglim That's amazing environment. I will see that world parameter!
Do you have any paper ?
Pretty cool!