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Adaptive Depth-Map-Guided Bundle Adjustment for Correspondence-Free Multi-View Point Cloud Registration

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

Robotic processing of irregular steel scrap requires dense 3-D measurement to replace manual visual assessment in hazardous cutting workcells. The reconstructed map is used to estimate piece dimensions, boundary geometry, feasible preheating and cutting regions, and collision-aware torch paths. The reconstruction errors therefore propagate directly to downstream measurement and planning. Existing multi-view registration methods commonly rely on feature extraction and data association to establish correspondences between views. In workcells with smooth metallic surfaces, repeated structures, oc

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