SLAM
[GNSS Localization](https://texonom.com/gnss-localization-3946a092737c4029b53c77f3afee88e3) 


## Simultaneous Localization and Mapping
우리가 Map을 만들기 위해서는 우리 위치가 어디있는지 알아야 한다
우리가 우리 위치를 알기 위해서는 Map이 필요
Mapping과 Localization은 서로 의존적
그래서 SLAM을 chicken-or-egg problem이라고
### SLAM Methods
|Title|
|:-:|
|[Graph based SLAM](https://texonom.com/graph-based-slam-b806e8a2b9554a35bad22cee4f663ec2)|
|[Kalman Filter](https://texonom.com/kalman-filter-d54f48bcbb934ac5a6afdc0c3776b830)|
|[Particle Filter](https://texonom.com/particle-filter-60dc91761cdd4e99bb540237cde25c2d)|

### SLAM Notion
|Title|
|:-:|
|[Probabilistic State Estimation](https://texonom.com/probabilistic-state-estimation-8c63a3e83763456dae32634964bc7913)|
|[NDT Algorithm](https://texonom.com/ndt-algorithm-780e7fbdb1d04b2c92b439c24a076372)|


### SLAM Systems
|Title|
|:-:|
|[Offline SLAM](https://texonom.com/offline-slam-ef060f1be36b4b8baa560a1b412db5fb)|
|[Online SLAM](https://texonom.com/online-slam-e7a7db5b9a234c6c8a244ba87b90107f)|



> [Slam 1강 (Introduction to SLAM) 요약](https://taeyoung96.github.io/slam/SLAM_01/)

> [SLAM KR](https://www.youtube.com/channel/UCXvT7auo7xUd7v0B2pmvwIA)





