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Loading...Introduction to Autonomous Navigation Systems
When I first started working with autonomous vehicles, I was surprised by the complexity of navigation systems. Last quarter, our team discovered that choosing the right SLAM algorithm can make or break the performance of an autonomous robot. In this article, I'll share our experience with ROS 2 and OpenCV 4.7, and provide a comparative study of Cartographer and Orb-SLAM3.
Background on SLAM Algorithms
SLAM (Simultaneous Localization and Mapping) algorithms are essential for autonomous navigation. They allow robots to build a map of their environment while simultaneously localizing themselves within that map. Most docs skip the hard part - implementing and optimizing these algorithms for real-world scenarios.
Cartographer: An Overview
Cartographer is a popular open-source SLAM library developed by Google. It's known for its high accuracy and efficiency.
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- Complete step-by-step implementation guide
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- Common mistakes to avoid
- Real-world examples and metrics
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