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Low Resolution Next Best View for Robot Packing

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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@article{preziosa2025_2505.04228,
  title={ Low Resolution Next Best View for Robot Packing },
  author={ Giuseppe Fabio Preziosa and Chiara Castellano and Andrea Maria Zanchettin and Marco Faroni and Paolo Rocco },
  journal={arXiv preprint arXiv:2505.04228},
  year={ 2025 }
}
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