Be the only one, not the best one

안녕하세요~ 저희 그룹에서 지난 반기동안 진행된 Sensor Fusion Study 관련 전체 유튜브 및 슬라이드쉐어 스터디자료를 깃헙으로 정리하여 공유드립니다. 🙂 스타 많이 눌러주세요~

마지막 시간에는 실제 센서퓨전이 현실에서 어떻게 응용되는지 imu/gps/radar/lidar/camera fusion 관련 작은 세미나도 가졌습니다. 그동안 훌륭하신 스터디 원분들과 함께해서, 지식적으로 성장 뿐만아니라 좋은 에너지와 보람을 느꼈던 시간이었습니다. 함께 잘 이끌어주신 hayden님 너무 감사드려요.

저희가 학습한 KF, EKF, UKF, H infinity Filter, Particle Filter 등을 kitti dataset 을 파싱해 python 코드로 직접 구현하는 스터디를 Sensor Fusion 2 에서 진행할 예정이니 많이 기대해주세요~


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Sensor Fusion Study Based on "Optimal State Estimation"

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README.md

Sensor Fusion Study

Sensor Fusion Study Based on "Optimal State Estimation - Dan Simon"

Sponsor by AI Robotics KR https://www.facebook.com/groups/airoboticskr/



Members

Study Lead :

Stella Seoyeon Yang @howtowhy, Hayden

Study Contributors :

Sora Kang, Dong Hyun Kim, Jeong Eun Park @jeongeun980906, Jin Hyuk Song @Jinhyeok1489, Young Beom Kim @eddy979797, Hae Gu Lee, Sung Min Ahn @aminsung, Soo Young Kim @kimsooyoung, Young Joo Kim, Kile

𝐂𝐡𝟏. 𝐋𝐢𝐧𝐞𝐚𝐫 𝐒𝐲𝐬𝐭𝐞𝐦 : Hayden

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch1-linear-system-hayden

Youtube : https://youtu.be/-6pO8G8PHC4

𝐂𝐡𝟐. 𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐓𝐡𝐞𝐨𝐫𝐲 : Seo Yeon Stella Yang

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-probability-theory-stella

Youtube :https://youtu.be/38dVDay2XnA

𝐂𝐡 𝟑. 𝐋𝐞𝐚𝐬𝐭 𝐒𝐪𝐮𝐚𝐫𝐞 𝐄𝐬𝐭𝐢𝐦𝐚𝐭𝐢𝐨𝐧 : Sora Kang, Stella, Hayden

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch3-least-square-estimation-stella-hayden

Youtube : https://youtu.be/C_gtrXk3zNo

𝐂𝐡𝟒. 𝐏𝐫𝐨𝐩𝐚𝐠𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐬𝐭𝐚𝐭𝐞𝐬 𝐚𝐧𝐝 𝐜𝐨𝐯𝐚𝐫𝐢𝐚𝐧𝐜𝐞 : Dong Hyun Kim

Slide: https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch4-propagation-of-states-and-covariance

Youtube:https://youtu.be/38dVDay2XnA

𝐂𝐡 𝟓. 𝐓𝐡𝐞 𝐃𝐢𝐬𝐜𝐫𝐞𝐭𝐞-𝐓𝐢𝐦𝐞 𝐊𝐚𝐥𝐦𝐚𝐧 𝐅𝐢𝐥𝐭𝐞𝐫: Jeong Eun Park

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch5-the-discretetime-kalman-filter

Youtube : https://www.youtube.com/watch?v=j9CRDGqmJ1I

𝐂𝐡 𝟔. 𝐀𝐥𝐭𝐞𝐫𝐧𝐚𝐭𝐞 𝐊𝐚𝐥𝐦𝐚𝐧 𝐅𝐢𝐥𝐭𝐞𝐫 𝐅𝐨𝐫𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬: Jin Hyuk Song

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch6-alternate-kalman-filter-formulations-jinhyuk-song

Youtube: https://www.youtube.com/watch?v=xtSLagWgG3g

𝐂𝐡 𝟕. 𝐊𝐚𝐥𝐦𝐚𝐧 𝐅𝐢𝐥𝐭𝐞𝐫 𝐆𝐞𝐧𝐞𝐫𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 : Young Beom Kim

Slide :https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch7-kalman-filter-generalizations

Youtube :https://youtu.be/y1T4ogYlJb0

𝐂𝐡 𝟖. 𝐓𝐡𝐞 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬-𝐓𝐢𝐦𝐞 𝐊𝐚𝐥𝐦𝐚𝐧 𝐅𝐢𝐥𝐭𝐞𝐫 : Hae Gu Lee

Slide :https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch8-the-continuoustime-kalman-filter

Youtube :https://youtu.be/HtS2SJcXcTE

𝐂𝐡 𝟗. 𝐎𝐩𝐭𝐢𝐦𝐚𝐥 𝐒𝐦𝐨𝐨𝐭𝐡𝐢𝐧𝐠: Hayden

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch9-optimal-smoothing-hayden

Youtube : https://youtu.be/Amm6pObx8No

𝐂𝐡 𝟏𝟎. 𝐀𝐝𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐓𝐨𝐩𝐢𝐜𝐬 𝐢𝐧 𝐊𝐚𝐥𝐦𝐚𝐧 𝐅𝐢𝐥𝐭𝐞𝐫𝐢𝐧𝐠: Stella Seoyeon Yang

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch11-additional-topic-in-kalman-filter-stella-seoyeon-yang

Youtube: https://youtu.be/TI_fV4t6pOU

𝐂𝐡 𝟏𝟏. 𝐓𝐡𝐞 𝐇-𝐈𝐧𝐟𝐢𝐧𝐢𝐭𝐲 𝐅𝐢𝐥𝐭𝐞𝐫 : Young Beom Kim

Slide :https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch11-the-hinfinity-filter

Youtube :https://youtu.be/I_Kuj3coyFI

𝐂𝐡 𝟏𝟐. 𝐀𝐝𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐓𝐨𝐩𝐢𝐜𝐬 𝐢𝐧 𝐇-𝐈𝐧𝐟𝐢𝐧𝐢𝐭𝐲 𝐅𝐢𝐥𝐭𝐞𝐫𝐢𝐧𝐠 : Hayden

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch12-additional-topics-in-hinfinity-filtering-hayden

Youtube :https://youtu.be/Y7xQXTdHKWw

𝐂𝐡 𝟏3. 𝐍𝐨𝐧𝐥𝐢𝐧𝐞𝐚𝐫 𝐊𝐚𝐥𝐦𝐚𝐧 𝐅𝐢𝐥𝐭𝐞𝐫𝐢𝐧𝐠 : Sung Min Ahn

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch13-nonlinear-kalman-filtering-ahn-min-sung

Youtube :https://youtu.be/xucMwb7yAwY

𝐂𝐡 𝟏4. 𝐓𝐡𝐞 𝐔𝐧𝐬𝐜𝐞𝐧𝐭𝐞𝐝 𝐊𝐚𝐥𝐦𝐚𝐧 𝐅𝐢𝐥𝐭𝐞𝐫 : Soo Young Kim

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch14-the-unscented-kalman-filter-sooyoung-kimg

Youtube :https://youtu.be/niHpxUUbZ6c

𝐂𝐡 𝟏5. 𝐓𝐡𝐞 𝐏𝐚𝐫𝐭𝐢𝐜𝐥𝐞 𝐅𝐢𝐥𝐭𝐞𝐫 : Stella Seoyeon Yang

Slide : https://www.slideshare.net/roboticskrai/sensor-fusion-study-ch15-the-particle-filter-seoyeon-stella-yang

Youtube :https://youtu.be/23QPRsIlJHk

Additional Session :

𝐑𝐞𝐚𝐥𝐰𝐨𝐫𝐥𝐝 𝐒𝐞𝐧𝐬𝐨𝐫 𝐅𝐮𝐬𝐢𝐨𝐧 𝟏 : Soo Young Kim, Stella Seoyeon Yang

Slide1:https://www.slideshare.net/roboticskrai/sensor-fusion-study-real-world-1-lidar-radar-fusion-kim-soo-young-237932335

Slide2:https://www.slideshare.net/roboticskrai/sensor-fusion-study-real-world-2-gps-ins-fusion-stella-seoyeon-yang-237976578Youtube :https://youtu.be/23QPRsIlJHk

Youtube : https://youtu.be/74bdIvTIjvY

𝐑𝐞𝐚𝐥𝐰𝐨𝐫𝐥𝐝 𝐒𝐞𝐧𝐬𝐨𝐫 𝐅𝐮𝐬𝐢𝐨𝐧 𝟐 : Young Joo Kim, Kile

Youtube :https://youtu.be/t-4bAf3woSU

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#3분슬램

안녕하세요, lidar slam 공부중인 김기섭입니다.

SLAM을 몰라도 한번 돌려보면 재밌어진다! 라고 평소에 생각하는데요.

3분이면 (녹화하는데는 16분 걸렸지만...)

따라해볼수 있는 A-LOAM 실습 영상을 찍어보았습니다.

https://youtu.be/Ea2sDqXf6ZY

특히 A-LOAM 원래 깃헙 리포에서는 velodyen lidar 에 대해서만 launch 파일이 준비되어 있어서

다른 lidar 에 대해 사용하고 싶을 때 어떻게 해야하는지 다뤄보았습니다.

MulRan dataset 에 있는 Ouster lidar 에 대해 사용해보았습니다.

이상입니다!

https://m.youtube.com/watch?feature=youtu.be&v=YPkSXTaGACA

#3분슬램

안녕하세요 좋은 일요일입니다!

visual slam 에서 현재 가장 큰 축으로 ORB-SLAM 와 DSO가 있는데요,

DSO 를 ros 에 물리는 과정이 리드미에서 크게 친절하지 않아서

한번 영상으로 찍어보았습니다.

https://youtu.be/YPkSXTaGACA

사실 돌려보는데 3분보다는 오래 걸리지만...

그만큼 쉽게 DSO도 한번 돌려보시면

SLAM이 재밌어질거라 믿습니다 !

감사합니다