PROSPECT: Precision Robot Spectroscopy Exploration and Characterization Tool
<|reference_start|>PROSPECT: Precision Robot Spectroscopy Exploration and Characterization Tool: Near Infrared (NIR) spectroscopy is widely used in industrial quality control and automation to test the purity and grade of items. In this research, we propose a novel sensorized end effector and acquisition strategy to capture spectral signatures from objects and register them with a 3D point cloud. Our methodology first takes a 3D scan of an object generated by a time-of-flight depth camera and decomposes the object into a series of planned viewpoints covering the surface. We generate motion plans for a robot manipulator and end-effector to visit these viewpoints while maintaining a fixed distance and surface normal. This process is enabled by the spherical motion of the end-effector and ensures maximal spectral signal quality. By continuously acquiring surface reflectance values as the end-effector scans the target object, the autonomous system develops a four-dimensional model of the target object: position in an $R^3$ coordinate frame, and a reflectance vector denoting the associated spectral signature. We demonstrate this system in building spectral-spatial object profiles of increasingly complex geometries. We show the proposed system and spectral acquisition planning produce more consistent spectral signals than naive point scanning strategies. Our work represents a significant step towards high-resolution spectral-spatial sensor fusion for automated quality assessment.<|reference_end|>
@article{hanson2024prospect:,
    title={PROSPECT: Precision Robot Spectroscopy Exploration and Characterization
  Tool},
    author={Nathaniel Hanson, Gary Lvov, Vedant Rautela, Samuel Hibbard, Ethan
  Holand, Charles DiMarzio, Tac{s}k{i}n Pad{i}r},
    journal={arXiv preprint arXiv:2403.17232},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.17232},
    primaryClass={cs.RO}
}