Robotics and Simulation
Benchmarking platform for robot localization systems
<p>Building localization and navigation systems requires a lot of time, effort and statistical analysis over multiple scenarios. There are multiple sparse tools out there to create specific KPIs around datasets but almost none that provide end to end integration test scenarios, KPIs and automatic report generation for localization systems.
Last year, at FOSDEM, we presented beluga - https://github.com/Ekumen-OS/beluga - a Monte Carlo Localization Framework for robotics. This year, we would like to present one of the tools we built for this project, Lambkin, the Localization and Mapping BenchmarKINg system that allows to orchestrate test runs of your code, data, KPIs and report generation all in one platform.
You can find the code here: https://github.com/Ekumen-OS/lambkin</p>
Additional information
| Live Stream | https://live.fosdem.org/watch/ub2147 |
|---|---|
| Type | devroom |
| Language | English |
More sessions
| 1/31/26 |
<p>Welcome session.</p>
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| 1/31/26 |
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| 1/31/26 |
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| 1/31/26 |
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| 1/31/26 |
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| 1/31/26 |
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| 1/31/26 |
<p>The learning curve for ROS2 can be steep, often requiring the installation and resolution of diverse software dependencies across operating systems, sensors, network configurations and robotic platforms. By combining virtual machines (VMs), with their off-the-shelf, ready-to-use environments resources and modern container registry workflows, we can reduce this complexity and enables learners to focus more directly on developing ROS2 skills. This approach also offers a smoother onboarding ...
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