hxxmin/SP-SLAM

SP-SLAM is a specialized academic implementation of Visual SLAM. Its primary contribution is the joint optimization of point and surface (planar) features, which typically improves performance in man-made environments (offices, corridors). However, from a competitive standpoint, the project is nearly dormant with only 24 stars and zero velocity over five years. It lacks the community and robustness of industry-standard frameworks like ORB-SLAM3, Kimera, or OpenVSLAM. The 'moat' here was originally the specific plane-extraction algorithms, but these are now standard in the robotics community. Furthermore, the field of SLAM is rapidly shifting toward 'Neural SLAM' and Gaussian Splatting-based mapping, making traditional geometric-only solvers like this one increasingly obsolete. While frontier labs (OpenAI/Anthropic) are unlikely to build a C++ plane-based SLAM tool, platforms like Meta (Quest/Orion) and Apple (VisionPro) have already integrated more advanced, proprietary versions of these capabilities into their OS. For a developer or investor, this repo serves as a historical reference implementation rather than a viable foundation for a new product.