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Loading...Introduction to Autonomous Navigation Systems
When I first started working on autonomous navigation systems, I was surprised by the complexity of the problem. Last quarter, our team discovered that our robot's navigation system was failing to map large areas efficiently. We tried using the default SLAM (Simultaneous Localization and Mapping) algorithm, but it was not accurate enough for our use case. Here's what I learned when trying to build a more efficient autonomous navigation system using ROS 2 Navigation and OpenCV 4.7.
Understanding SLAM Algorithms
SLAM algorithms are used to create a map of an unknown environment while simultaneously localizing the robot within that environment. Most docs skip the hard part - implementing SLAM in a real-world scenario. I realized that the key to a successful SLAM implementation is choosing the right algorithm and tuning its parameters for your specific use case.
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