Object Tracking via Sensor Fusion

版本 1.0.1 (19.5 KB) 作者: Andrei Moraru
Learn linear, extended and unscented Kalman filters in a fun, interactive way
73.0 次下载
更新时间 2023/2/28

Can you outrun the Big Bad Kalman filter ?

Some linear, extended and unscented movement tracking Kalman filters, with a fun twist

View Object Tracking via Sensor Fusion on File Exchange

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Run ObjectTracker.m and make sure all files are in the same directory. Set your scenarios using the dropdowns.

Press Play and enjoy :-)

Go for Developer Mode if you want to generate your own custom data and play around with the trackers:

Model Parameters Filter Tuning Extra Sensor
1 2 3

Note You can control the Seal if you own an Arduino + MPU IMU sensor suite, this is how it works.

To achieve this, you may choose Command Driven instead of Simulation for the Running Mode.

Demos

Noob level: defeat the linear Kalman filter

The Shark can only chase you in a linear fashion

Test each of your runs:

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Experienced: defeat the extended Kalman filter

The Shark is getting help from a Seagull, who acts like a sensor for detecting your non-linear movements

Measure your performances:

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Note You can trick the shark by moving fast in a non-linear manner

This way you can make the filter diverge due to wrong partial derivative computation

Legendary: defeat the unscented Kalman filter

No more linear covariance transforms, the Shark has unlocked the Unscented Transform ability

And see how far your can get:

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How this madness was designed:

engineered:

and programmed:

with the following workflow:

and if you made it this far...

here is the whole thing explained in detail (Vampire language):

OneFilterToRuleThemAll.pdf

引用格式

Andrei Moraru (2025). Object Tracking via Sensor Fusion (https://github.com/AndreiMoraru123/2D-Tracker), GitHub. 检索时间: .

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版本 已发布 发行说明
1.0.1

Hi! I had actually left some personal file paths so the code would crash on other machine. I commented them out

1.0.0

要查看或报告此来自 GitHub 的附加功能中的问题,请访问其 GitHub 仓库
要查看或报告此来自 GitHub 的附加功能中的问题,请访问其 GitHub 仓库