Sonar SLAMExpert
BatSLAM 2.0: Sequence-Verified Sonar Place Recognition in a Robust Pose Graph
BatSLAM 2.0 is a preprint describing a sonar-only simultaneous localization and mapping system that uses a biomimetic binaural acoustic front-end, sequence-verified place recognition, and a factor-graph pose graph. In 12 simulated long-range drives with calibrated odometry, it produced consistent maps with no wrong loop closures and a post-alignment trajectory error of 0.18–0.53 m; on a real beamformed sonar recording, it cut error from 3.62 m to 0.67 m. This matters for robots that must operate in darkness, smoke, or dust where cameras and lidar fail.