Gait-Conditioned Multi-View LiDAR Reconstruction for Occluded Shelf Inspection

Abstract

Paper I of ORIA’s Onboard volume on legged active perception for warehouse inventory (Unitree Go2). Rather than treating a quadruped’s gait-induced bobbing, pitch, and roll as noise to be filtered, this work exploits locomotion as a controlled source of viewpoint diversity: motion-corrected LiDAR sweeps are aggregated across gait phases to build a probabilistic visibility field that recovers deep-shelf geometry occluded from any single static scan. The central claim is observability — which shelf volumes become visible because of motion — rather than deblurring, validated in Isaac Lab against static and stabilized-trajectory baselines. Full paper linked once it completes review.