Problem

Build a SLAM system that can use 360-degree imagery for mapping and localization across a wide range of environments, especially where large fields of view and long trajectories matter.

Method

The project uses a panoramic SLAM pipeline with feature extraction and matching on 360 imagery, pose graph optimization, loop closure detection, and global refinement to maintain consistent maps over large-scale scenes.

Focus

  • Robust localization from panoramic observations
  • Loop closure and drift reduction
  • Globally consistent maps from long trajectories

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