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feat: implement fine registration algorithms (ICP variants and NDT)
Implemented 5 fine registration algorithms for precise point cloud alignment: - Point-to-Point ICP: Classic ICP using SVD for transformation estimation - Point-to-Plane ICP: ICP variant using surface normals for better convergence - Generalized ICP: Plane-to-plane ICP with local covariance modeling - AA-ICP: Anderson Acceleration enhanced ICP for faster convergence - NDT: Normal Distributions Transform for robust registration Key features: - CRTP-based design following the existing architecture - Support for parallel optimization (configurable) - Comprehensive unit tests and performance benchmarks - Fixed convergence checking in base class to skip first iteration - Added proper normal computation for Point-to-Plane ICP - Adjustable parameters for each algorithm Note: AA-ICP implementation has known issues and needs further debugging. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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‎benchmark/CMakeLists.txt‎

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pcl/descriptors_benc.cpp
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pcl/correspondence_benc.cpp
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pcl/registration_benc.cpp
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pcl/fine_registration_benc.cpp
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${CMAKE_SOURCE_DIR}/test/my_catch2_main.cpp
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