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arXiv · 2505.04228

Low Resolution Next Best View for Robot Packing

Giuseppe Fabio Preziosa·Chiara Castellano·Andrea Maria Zanchettin·Marco Faroni·Paolo Rocco
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Abstract

Automating the packing of objects with robots is a key challenge in industrial automation, where efficient object perception plays a fundamental role. This paper focuses on scenarios where precise 3D reconstruction is not required, prioritizing cost-effective and scalable solutions. The proposed Low-Resolution Next Best View (LR-NBV) algorithm leverages a utility function that balances pose redundancy and acquisition density, ensuring efficient object reconstruction. Experimental validation demonstrates that LR-NBV consistently outperforms standard NBV approaches, achieving comparable accuracy with significantly fewer poses. This method proves highly suitable for applications requiring efficiency, scalability, and adaptability without relying on high-precision sensing.

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Giuseppe Fabio Preziosa, Chiara Castellano, Andrea Maria Zanchettin, Marco Faroni, Paolo Rocco. 2025-05-07. Low Resolution Next Best View for Robot Packing. https://doi.org/10.1016/j.ifacol.2025.10.228

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