Abstract: Methods and systems for a materials handling vehicle comprising a processor and a sensor to record warehouse features. The processor is configured to generate and extract features from sensor data, create a factor graph (FG) including a sensor extrinsics node (e0), and generate an initial vehicle node (v0), initial sensor frame node (c0), and initial sensor feature node (f0) that comprises a selected extracted feature associated with c0 and v0 in an initial data association. A subsequent vehicle node (v1) is generated based on an accumulated odometry amount, and a subsequent sensor frame node (c1) is generated and associated with e0, v1, and one of f0 or a subsequent sensor feature node (f1) in a subsequent data association. The FG is optimized to provide a sensor calibration output based on the data associations, and the vehicle is navigated based on the sensor calibration output.

Abstract: Methods and systems for a materials handling vehicle comprising a processor and a sensor to record warehouse features. The processor is configured to generate and extract features from sensor data, create a factor graph (FG) including a sensor extrinsics node (e0), and generate an initial vehicle node (v0), initial sensor frame node (c0), and initial sensor feature node (f0) that comprises a selected extracted feature associated with c0 and v0 in an initial data association. A subsequent vehicle node (v1) is generated based on an accumulated odometry amount, and a subsequent sensor frame node (c1) is generated and associated with e0, v1, and one of f0 or a subsequent sensor feature node (f1) in a subsequent data association. The FG is optimized to provide a sensor calibration output based on the data associations, and the vehicle is navigated based on the sensor calibration output.