SonicSense: Object Perception from In-Hand Acoustic Vibration
<|reference_start|>SonicSense: Object Perception from In-Hand Acoustic Vibration: We introduce SonicSense, a holistic design of hardware and software to enable rich robot object perception through in-hand acoustic vibration sensing. While previous studies have shown promising results with acoustic sensing for object perception, current solutions are constrained to a handful of objects with simple geometries and homogeneous materials, single-finger sensing, and mixing training and testing on the same objects. SonicSense enables container inventory status differentiation, heterogeneous material prediction, 3D shape reconstruction, and object re-identification from a diverse set of 83 real-world objects. Our system employs a simple but effective heuristic exploration policy to interact with the objects as well as end-to-end learning-based algorithms to fuse vibration signals to infer object properties. Our framework underscores the significance of in-hand acoustic vibration sensing in advancing robot tactile perception.<|reference_end|>
@article{liu2024sonicsense:,
    title={SonicSense: Object Perception from In-Hand Acoustic Vibration},
    author={Jiaxun Liu, Boyuan Chen},
    journal={arXiv preprint arXiv:2406.17932},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.17932},
    primaryClass={cs.RO cs.MM cs.SD eess.AS}
}